MACHINE LEARNING ENGINEER SKILLS, EXPERIENCES, AND JOB REQUIREMENTS
Reviewed by Lam Nguyen under Editorial Standards
Published: Mar 10, 2026. The Machine Learning Engineer has experience developing and deploying scalable machine learning systems using Python, modern ML/DL frameworks, big data technologies, and cloud platforms. This role requires strong knowledge of machine learning theory, statistics, data engineering, distributed systems, and software engineering best practices such as CI/CD and MLOps. The engineer also demonstrates the ability to build robust production-ready models, work with large and diverse datasets, and collaborate effectively to deliver data-driven solutions.
Essential Hard and Soft Skills for a Machine Learning Engineer Resume
- Machine Learning
- Deep Learning
- AWS Cloud
- Data Pipelines
- MLOps Practices
- Model Deployment
- Computer Vision
- Natural Language Processing
- Big Data Processing
- Kubernetes Orchestration
- Cross-Functional Collaboration
- Stakeholder Communication
- Technical Leadership
- Problem Solving
- Strategic Thinking
- Research Mindset
- Agile Adaptability
- Mentorship
- Business Alignment
- Continuous Learning
Summary of Machine Learning Engineer Knowledge and Qualifications on Resume
1. BS in Software Engineering with 6 years of Experience
- Experience developing and deploying machine learning systems into production
- Strong experience working with a variety of relational SQL and NoSQL databases
- Strong experience working with big data tools (Hadoop, Spark, Kafka, etc.)
- Experience with at least one cloud provider solution (AWS, GCP, Azure)
- Strong experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Industry experience building innovative end-to-end Machine Learning systems
- Ability to quickly prototype ideas and solve complex problems by adapting creative approaches
- Experience working with distributed systems, service-oriented architectures and designing APIs
- Strong knowledge of data pipeline and workflow management tools
- Expertise in standard software engineering methodology, e.g., unit testing, test automation, continuous integration, code reviews, design documentation
2. BS in Computer Science with 5 years of Experience
- Expertise in Python and its ecosystem
- Detailed understanding of machine learning, software engineering and distributed computing basics
- Experience with DBMS and different data models (relational, columnar, document, etc.)
- Competency in building HTTP-based APIs for distributed systems
- Experience with machine learning tools such as Pandas, Numpy, Scikit-Learn, TensorFlow, PyTorch, DeepAR, Prophet, Catboost, XGBoost, Spark, PySpark and tasks such as Time Series forecasting, Computer Vision, Recommendation Systems
- Understanding how web applications are built and organized
- Experience with continuous integration and continuous development
- Strong Python skills
- Background in Machine Learning with proficient knowledge of MLOps tools, e.g., Kubernetes, Django, Docker
- Experience transforming research prototypes into robust and scalable products running on cloud infrastructure or edge devices
- Good soft and communication skills
3. BS in Electrical Engineering with 7 years of Experience
- Strong ability to problem solve, apply lateral thinking and work autonomously
- Must have tertiary qualifications in a relevant field (e.g., computer science, data science, mathematics, statistics)
- Demonstrate statistical inference and decision intelligence with quantifiable data-driven evidence
- Demonstrate working knowledge of the main components of cloud-based data environments
- Demonstrate the application of SQL fundamentals to support the exploration and profiling of data
- Demonstrate solid object orientated python coding including classes, inheritance, functions, loops, dictionaries, and lists
- Demonstrate manipulation of Spark dataframes
- Production experience in the implementation of feature engineering and data pre-processing techniques
- Understand and apply the fundamentals of supervised classification and prediction (regression) models and unsupervised clustering models
- Must have created models using deep neural networks and understand the theory of the network used
- Demonstrated the principles of model training, testing, generalisation, and validation techniques based on the type of model being deployed
- Able to design and implement ML/AI Ops, version control, CI/CD pipelines and automation of test plans
4. BS in Computer Engineering with 3 years of Experience
- Experience and eagerness for further development in camera and/or LiDAR-based perception algorithms
- Strong Interpersonal skills, including proactive deadline management and pointed stakeholder communications
- Ability to program in Pytorch, Python,
- Ability to research and implement the latest cutting-edge AI technologies
- High proficiency in fundamental technical skills (Programming language like Java/Python/R database language like SQL
- Strong UNIX background
- Working knowledge of Hadoop, Map-Reduce, Hive, Pig)
- Experience with one or more deep learning libraries and platforms (e.g., TensorFlow, PyTorch, etc)
5. BS in Mathematics with 5 years of Experience
- Experience doing quantitative analysis and using complex statistical models
- Strong programming and data analytics skills
- Expert understanding of git, Python and at least one deep framework such as TensorFlow / Keras or PyTorch
- Up-to-date knowledge of machine learning techniques, general deep learning and predictive modelling
- Strong understanding of Google Cloud Platform, DevOps and software development tools
- Expertise in Data Ingestion / Processing and Modelling
- Able to express complex data needs and understand data quality-cleansing processes and methods
- Extensive corporate data knowledge
- Aware of critical company business processes and underlying data
- Fluency in SQL for writing efficient queries on large datasets
- Good knowledge of the Linux operating system
- Ability to write robust code in Python, Java and R
6. BS in Information Technology with 4 years of Experience
- Strong computer science fundamentals, algorithms, and data structures background
- Experience programming in Python
- Strong knowledge of ML/DL fundamentals and techniques
- Proven experience in applied ML/DL, computer vision, natural language processing, and/or audio processing
- Experience working with any of the following ML/DL frameworks: Tensorflow, Pytorch
- Experience working in agile teams following SCRUM or KANBAN
- Processes and applications of artificial perception in robotics (UGV and/or UAV)
- Previous experience working in start-ups
7. BS in Applied Statistics with 8 years of Experience
- Deep knowledge in at least one field of ML through graduate degrees, or through equivalent professional experience
- Proficient in software development and understanding of coding best practices
- Familiarity with code reviewing, version control systems, good code hygiene, documentation, etc.
- Good written and oral communication skills in communicating with a mixed technical and non-technical audience
- Experienced in working within a team to successfully deliver an ML solution
- Experience in solving problems in healthcare or biomedical settings
- Experience in working with varied data modalities, including time series, images, natural language text, genomics, speech, etc.
- Cloud-based development experience
- Experience in working with problems in both data-deficient and large-scale data settings
- Experience in working within cross-disciplinary and cross-functional teams
- Demonstrated track record of developing novel, state-of-the-art ML methods through peer-reviewed publications or patent filings
- Experience in ML and software development
8. BS in Machine Learning with 5 years of Experience
- Good experience as a Machine Learning or backend Software Engineer
- Strong experience with Python and standard Python ML libraries (PyTorch, TensorFlow, Numpy, Pandas)
- Knowledge of Data Engineering and Machine Learning
- Ability to work in an international environment and communicate in English
- Strong team spirit
- Experience in DevOps and MLOps
- Experience working with distributed frameworks (Spark, Dask, etc.)
- Knowledge in ML / DL (e.g., convolutional neural networks, generative models, recurrent neural networks, transformers), AI-based recommender systems, data mining and clustering, and predictive modelling to apply these techniques on real-world problems
- Ability to do exploratory analysis on large volumes of data and find key descriptive and inferential properties
- Strong skills in software engineering practices with expertise in applicable programming languages and frameworks such as Python, C++, scikit-learn, XGBoost, Pytorch and Tensorflow, respectively
9. BS in Robotics Engineering with 6 years of Experience
- Experience in C++(main language)/Python languages
- Basic practical experience in machine learning/data science
- Knowledge of Windows and Linux development environments
- Knowledge of Intel development tools and libraries
- Knowledge of development on GPU
- Excellent coding skills and software development experience
- Must be proficient with Python, Spark or Scala
- Strong background in Machine Learning
- Knowledge of retrieval and ranking (leveraging deep learning)
- Able to build machine learning models in Python (with some work in Spark)
- Excellent communication/ collaboration skills
10. BS in Computational Physics with 4 years of Experience
- Experience as a machine learning engineer
- Experience in Python programming
- Familiarity with Sklearn, Tensorflow, Keras, or Pytorch
- Experience in database and SQL
- Good to have an understanding of the AWS ecosystem (MWAA, Redshift, Athena, S3, Glue, etc.)
- Understanding of data warehouse and data lake
- Understanding of CI/CD pipeline (Jenkins, Gitlab, Github, etc.)
- Superb analytical and problem-solving abilities
- Great communication and collaboration skills
- Excellent time management and organizational abilities
11. BS in Electrical Engineering with 7 years of Experience
- Passion for green technology
- Excellent communication and organization skills
- Independent and proactive, especially in building new products
- Prior experience with Python and Python unit and integration tests
- Prior experience with a Python machine learning library, such as TensorFlow, Keras, PyTorch, or SciKit
- Prior experience building and pushing time-series forecasting algorithms to a production environment
- Prior experience working on team-based software
- Proficiency in developing extensible, object-oriented software using test-driven development techniques
- Experience with Git version control
- Mathematical understanding of linear programming and optimization
- Knowledge of power, energy, and electrical physics
- Familiarity with utility markets, programs, and tariffs
- Familiarity with Jira
12. BS in Computer Science with 5 years of Experience
- Production coding experience and comfort with an on-call rotation
- Previous experience in machine learning and statistics fundamentals
- History of developing production APIs, implementing robust tests, and using profiling or telemetry tools
- Comfort implementing, resourcing, and debugging PySpark workflows
- Aptitude with data storage and caching, such as SQL and Redis
- Experience with production-ready machine learning packages such as scikit-learn or SparkML
- Strong understanding of SQL and NoSQL
- Experience working with Hadoop or Spark and AWS, GCP, or Azure
- Understanding of a Linux environment
- Knowledge of the data pipeline
- Passionate about building exciting solutions and growth opportunities
13. BS in Data Science with 4 years of Experience
- Knowledge of cloud systems such as AWS, Azure, GCP and containerisation such as Docker
- Experience working with large, real-world datasets
- Demonstrated in-depth understanding of product development lifecycle
- Demonstrated aptitude for and interest in peer mentorship
- Experience deploying code into production through CI/CD tools
- Knowledge of biostatistics/life sciences/healthcare technology
- Knowledge of UX principles
- Experience working in the Hadoop ecosystem
- Prior working experience in management training
14. BS in Computer Engineering with 2 years of Experience
- Self-driven, critical thinker with an entrepreneurial mindset
- Prior startup experience
- Excellent communication skills, both verbal and written
- Prior experience solving computer vision problems such as object detection and image classification
- Experience in Medical device design engineering
- Experience working within an ISO 13485 QMS system
- Hands-on approach to problem-solving
- Self-directed, detail-oriented, and enjoy figuring out the most important problem to work on
15. BS in Data Engineering with 7 years of Experience
- Experience using one or more machine learning frameworks such as scikit-learn, PyTorch, TensorFlow and Keras
- Excellent communication, presentation, and documentation skills
- Experience with optimization, estimation algorithms, distributed algorithm design, and hands-on implementation of these techniques
- Ability to serve as a technical lead such as building technical requirements, software design, implementation, and clear communication
- Experience implementing end-to-end data science and machine learning projects
- Professional handling of Python and SQL
- Demonstrable experience with machine learning models
- Proficiency in mainstream deep learning frameworks
- Experience with cloud computing and GPU-accelerated environments
- Demonstrable experience working with state-of-the-art deep learning architectures
- Knowledge of the main components of a machine learning project pipeline, including data wrangling, feature engineering, training and evaluation
16. BS in Machine Learning with 5 years of Experience
- Demonstrated industry experience deploying Tensorflow, PyTorch, MXNet, and/or Keras models to a production environment for inference and/or automated model retraining,
- Depth of knowledge leveraging Kubeflow, Apache NiFi, Apache Airflow, AWS Step Functions, directed acyclic graphs (DAG), or other algorithmic pipeline orchestration architectures,
- Expert on CI/CD software best practices and using an agile framework for software deployment,
- Fluent in GoLang and Python
- Experience with Deep Learning
- Thrives in a fast-paced startup environment
- Passionate about the fintech and e-commerce markets
- Experience with deep learning and neural networks
- Experience with Lambda, Step Functions, AWS cloud development
- Experience in fintech, banking, or digital advertising industries
17. BS in Robotics Engineering with 6 years of Experience
- Knowledge to model and simulate systems to test algorithms for suitability
- Knowledge of a broad set of algorithms and applied math
- Must know Big Data techniques and tools
- Must have experience of high level software languages (e.g., Java, C/C++, etc.)
- Must know scripting languages (e.g., MATLAB, Python, Bash, etc.)
- Knowledge of simulation tools and model-based design (e.g., Simulink)
- Ability of unit testing and software validation techniques
- Possess knowledge of application lifecycle management tools (e.g., DOORS, PTC Integrity, TFS)
- Knowledge of source control systems (e.g., Git, Subversion)
- Ability to work with software configuration management processes and workflows
- Knowledge of software development standards/guidelines (e.g., CMMI)
- Knowledge of heavy machinery or automotive
- Must possess the ability to write specifications that describe software function
- Prior experience in reading and interpreting documents such as safety rules, operating and maintenance manuals, procedure manuals, and software specifications
- General Competencies Of The Machine Learning Engineer
18. BS in Computer Science with 5 years of Experience
- Experience in technology development in the field of image/video processing for autonomous vehicles and/or robotic systems
- Proficient in C, C++ and Python programming
- Familiar with Windows and Linux programming environments
- Familiar with ROS, OPENCV library
- Experience in applying Deep Learning Networks to solve computer vision problems
- Experience in embedded systems implementation, such as ARM, DSP or FPGA
- Experience in a similar role as a Machine Learning Engineer, Software Engineer with Computer Vision experience, etc.
- Experience in building and evaluating machine learning and deep learning models
- Experience putting machine learning models into production (GCP, AWS)
- Fluency in Python
19. BS in Data Science with 4 years of Experience
- Project experience in machine learning and statistical modeling
- Hands-on experience in building data science applications and machine learning pipelines
- Working knowledge of one or more SQL languages: Oracle, MySQL, PostgreSQL, Redshift, etc.
- Development experience in at least one programming language: Python, Java, C++, etc.
- Knowledge of common machine learning and statistics frameworks and concepts
- Experience with large data sets, distributed computing and cloud computing platforms
- Working experience in MLOps
- Experience with Automation tools like Airflow
- Must have Salesforce experience/certification
20. BS in Electrical Engineering with 7 years of Experience
- Previous working in machine learning engineer
- Previous work in a software/machine learning engineering role
- Strong expertise in A/B testing
- Able to drive causal impact using A/B testing
- Experience with recommender and/or ranking systems
- Solid theoretical knowledge of Machine Learning and Statistical concepts, including Deep Learning, as well as performance tradeoffs
- Strong hands-on experience with the standard Python DS stack
- Able to write clean and production-ready code
- Experience in collaborating across cross-functional teams including analytics and product management
- Working proficiency in English
- Experience with ML automation stack (MLFlow, Kubeflow, etc)
- Experience with smart Feed development
- Experience with Kubernetes and Docker
21. BS in Applied Mathematics with 6 years of Experience
- Hands-on experience in a similar role at a company using cutting-edge ML tools and Deep Learning research, Computer Vision or NLP
- Sound mathematical knowledge (linear algebra, probability theory, stats, matrix calculus)
- Reasonable understanding of theoretical ML principles, e.g., optimization, representation learning, generalization, topics such as semi-supervised or adversarial learning, image classification, object detection, segmentation
- Familiarity with Python and ideally one more programming language
- Experience with Deep Learning / Scientific tools, e.g., PyTorch, TF/Keras/JAX, SciKit Learn, Numpy, Pandas, OpenCV, etc.
- Creative thinker, problem solver and a willingness for continual learning
- Excellent communication, listening and presentation skills with diverse audiences and experience supporting and mentoring peers
- Experience with orchestration platforms (Kubernetes, containerization, and microservice design)
- Familiarity with distributed systems and architectures, test-driven development, CI/CD
- Previously published research papers in deep learning or other related fields
22. BS in Mathematics with 5 years of Experience
- Strong programming skills in languages like C++, Python, Java, Scala, Rust, or Go
- Experience with one or more of the following: PyTorch/PyTorch Lightning, TensorFlow, JAX
- Experience with cloud computing and infrastructure including Amazon Web Services (AWS) and distributed computing libraries like Apache Spark
- Experience with containerization and orchestration tools like Docker, Singularity, and Kubernetes
- Experience with deploying and maintaining deep learning systems and services in production at scale, including using MLOps frameworks like Weights and Biases
- Experience developing and maintaining codebases and software libraries, following industry best practices
- Strong background in statistics and machine learning, with experience in designing, building, and testing models
- Hands-on experience implementing production machine learning systems at scale
- Experience with data pipeline tools like Apache Beam and cloud platforms like GCP or AWS
23. BS in Applied Statistics with 8 years of Experience
- Proficient with Python
- Experience with PyTorch, TensorFlow, pyAudioAnalysis, librosa, and OpenCV (or similar)
- Experience with large-scale machine learning projects
- Knowledge of emotion recognition and speech recognition
- In-depth understanding of SOTA Machine Learning principles
- Excellent communication and teamwork skills
- Experience in defining and managing research projects with academia
- Experience in Software Development
- Experience programming in languages such as Python or Java
- Experience with Machine Learning in academia or industry
- Experience with Unix/Linux environments
- Proficient in programming languages: C/C++, Python, familiar with shell
- Good knowledge of Linux/Android development environment and tools
- Ability to customize and extend various machine learning frameworks, such as TensorFlow, and so on
- Familiar with optimization theory, such as convex optimization, numerical optimization, nonlinear programming, graph optimization, etc.
- Familiar with machine learning mathematics, related knowledge, probability and statistics, functional analysis, etc., open source contributions with high stars
24. BS in Data Engineering with 7 years of Experience
- Strong proficiency with Java, Python, Scala or C++
- Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing
- Advanced knowledge of performance, scalability, enterprise system architecture, and engineering best practices
- Experience with computer science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
- Hands on development experience with at least, one modern programming language such as Java, C++, C#, Scala, etc.
- Strong mathematical background and interest,
- Good confidence in using the Python ecosystem for efficient prototyping of ideas
- Strong interest and skills in software engineering and object-oriented programming (ideally in C++), allowing to integrate algorithms within a complex software framework
- Eagerness to be part of a high-skilled, dynamic team where talent is both challenged and supported
- Fluency in English and ideally German (or willingness to learn German)
- Industry experience building production web-scale systems that support Machine Learning models
- Expertise with Python
- Hands-on experience with Spark or a similar distributed framework
25. BS in Machine Learning with 5 years of Experience
- Deep knowledge of statistical methods and machine learning, with special emphasis on deep learning algorithms
- Experience in algorithms, machine learning, data science, or statistics
- Experience solving problems using Machine Learning Frameworks (e.g., PyTorch, TensorFlow)
- Experience with Big Query
- Comfortable with writing complex SQL queries for data retrieval and transformation
- Proficient in Python / Pyspark
- Prior experience in management consulting and/or analytics-based consulting
- Practical experience in designing and implementing deep neural network-based speech processing algorithms (e.g., Tensorflow, PyTorch)
- Strong programming skills in Python
- Working knowledge of Docker and Git
- Experience with Google Cloud Platform infrastructure
- Excellent problem-solving, communication, and collaboration skills
26. BS in Artificial Intelligence with 4 years of Experience
- Expertise in working with big data sets and ETL
- Strong understanding of Machine Learning concepts
- Knowledge of professional software engineering practices, best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems
- Proficiency with additional programming languages
- Experience building complex, large-scale distributed software systems
- Good knowledge of software engineering best practices
- Good knowledge of statistics
- Knowledge in deep learning and machine translation
- Understanding of the explore-exploit trade-off, and associated algorithms
- Experience in A/B testing
27. BS in Robotics Engineering with 6 years of Experience
- Very good knowledge of C++
- Practical knowledge of CI tools (git, CMake, Jenkins, github, GitLab)
- Ability to learn and acquire new knowledge quickly
- Good self-reliant skills, especially the ability to solve complex technical problems quickly
- Good command of English
- Experience leading large-scale projects that directly impact a similar business
- History using Python for machine learning model development and deployment
- Commercial experience building machine learning models into production settings
- Prior experience leading business-critical projects
- History of owning the machine learning lifecycle from end-to-end
28. BS in Computer Science with 5 years of Experience
- Experience in Software Engineering
- Solid understanding of Math and CS fundamentals
- Strong analytical skills
- Practical experience in Deep Learning (applying ML to real-world projects)
- Experience in Natural Language Processing
- Able to perform applied research projects and bring them to production
- Experience with one or more general-purpose languages (Java, C/C++, Python, etc.)
- Professional experience with Tensorflow/Pytorch or other popular ML frameworks
- Demonstrated ability to write high-quality code
- Team player with strong communication skills
- Proficiency in the written and spoken English language
29. BS in Data Science with 4 years of Experience
- Advanced degree in a quantitative discipline (i.e., computer science, applied mathematics, statistics, etc.) or equivalent experience
- Enterprise machine learning experience, designing and deploying models at scale using software development best practices
- Working experience in Python development
- Experience with Data Mining
- Experience with Data Modeling and notebook-based Data Science workflow
- Experience with either one of Tensorflow, Pytorch, Theano, or any other equivalent
- Experience with deploying models for real-time inference or batch processing
- Experience using some of the following: AWS, FastAPI, SQLAlchemy, Alembic, Docker
- Experience with Enterprise SaaS
30. BS in Electrical Engineering with 7 years of Experience
- Prior experience in any mix of Software development / Research / Data Science
- Great communication skills and a collaborative mindset
- Experience with Python
- Working knowledge of SQL
- Familiar with ML/Data Science libraries, e.g., Sklearn, Pandas, Numpy, Tensorflow, Spacy
- Interacting with cloud-based computing and storage resources
- Enjoys the entire process, i.e., understanding the business problems, gathering/extracting data, cleansing it, performing statistical analysis and everything in between
- Professional experience building analytics for geospatial data, satellite data, aerial imagery, LiDAR
- Experience with deep learning, computer vision, or photogrammetry
- Experience with geospatial technologies (e.g. PostGIS, GDAL/OGR, Rasterio, Shapely, GeoPandas, etc).
- Experience with workflow management engines (i.e., Luigi, Airflow, Pachyderm, etc.)
- Experience with automated deployment of models at scale
- Experience building APIs
- Working knowledge or experience shipping code with Kubernetes
- Experience using Spark or equivalent
- Cross-functional skills in data science, engineering or GIS, or work experience in customers’ industries (DoD, energy, insurance to start)
31. BS in Applied Mathematics with 6 years of Experience
- Experience with cloud computing platforms such as AWS or GCP
- Experience with Kubernetes
- Fluent in spoken and written English
- Good communication skills to express ideas and opinions
- High-quality standards of coding
- Programming experience with at least one software programming language
- Experience in software development
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
- Experience in building large-scale machine-learning infrastructure for online recommendation, ad ranking, personalization, or search, etc.
- Experience with ML libraries/frameworks such as Tensorflow, AWS Sagemaker, Keras, PyTorch, etc.
- Experience with Big Data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza
32. BS in Mathematics with 5 years of Experience
- Working experience as a data scientist, data engineer, or machine learning engineer, besides studies
- In-depth understanding of data science and proven affinity with data engineering (or vice versa)
- Solid programming experience in Python
- Proficiency in SQL, Git, command line, Docker, and API frameworks
- Proven experience in building models ready for production
- Knowledge of statistics and mathematics
- Ability to teach and learn from teammates
- Experience delivering applied machine learning products, including taking a product through design, implementation, and production
- Familiarity with Python (including NumPy, SciPy, Pandas), JVM, and Linux
- Familiarity with a variety of modeling techniques including classical and deep learning
- Experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems
33. BS in Artificial Intelligence with 4 years of Experience
- Working relatively autonomously but also having close interaction with the rest of the development team
- Extensive experience in Python
- Proven experience in machine learning theory and practice, through previous work, published research, high placement in relevant online competitions (i.e., Kaggle), post-graduate studies, or some advanced online course
- Computer Science/Engineering degree (or STEM with a heavy element of computer science)
- Prior experience with eHealth
- Working experience in Industry/full-time Machine Learning or Data Science
- Experience with TensorFlow, PyTorch, and Keras
- Strong programming skills in Python
- Database experience in SQL or MongoDB
34. BS in Data Engineering with 7 years of Experience
- Software engineering experience across multiple languages such as Python, Java, C/C++, R, Scala
- Extensive experience with cheminformatics tools and platforms such as JChem, RDKit, OpenBabel, Pipeline Pilot, KNIME, MOE, or Schrödinger
- Experience with predictive drug development methods, such as pharmacophore models, crystal structure-based models, QSAR methods, or free energy calculations
- Experience with standard statistical analysis and machine learning techniques
- Experience with popular analytical tools such as Pandas, Scikit-learn, Tensorflow, PyTorch, Jupyter, or ggplot2
- Experience with scalable analysis tools and platforms such as Hadoop, Spark, AWS, or GCP
- Exercise excellent oral and written communication skills, conveying new ideas to team and in touchpoints with product managers, healthcare experts, and partners in healthcare start-ups
- Demonstrate high initiative and are self-driven to excellence
- Embody a growth-mindset and are excited to receive feedback and continuously learn to deepen their understanding of ML and improve their interpersonal skills
- Demonstrate deep understanding in at least one subfield of ML and contribute knowledge to other team members
35. BS in Robotics Engineering with 6 years of Experience
- Demonstrated mastery in communication of technical ideas to non-technical audiences
- Ability to translate customer goals into practical engineering solutions
- Good understanding of foundational statistics concepts and algorithms: linear/logistic regression, random forest, boosting, NNs, etc.
- Passion for learning (new problem domains, algorithms, tools, etc.) and for analyzing data
- Strong programming skills with fluency in at least one of Python, Java, Scala, C/C++
- Familiar with industry-standard software engineering practices and systems knowledge
- Working knowledge of Unix/Linux systems
- Ability to access, manage, transfer, integrate and analyze complex datasets, especially using SQL
- Familiarity with libraries such as pandas, TensorFlow, scikit-learn
- Industry experience in software engineering and data science
- Experience working on large data sets, especially with Spark
- Experience with Python and Java
Professional Skills FAQs
What are professional skills?
Professional skills are abilities that help individuals perform tasks effectively in a workplace environment. These skills include both technical competencies required for specific roles and soft skills such as communication, teamwork, and problem solving.
What is the difference between hard skills and soft skills?
Hard skills are technical abilities learned through education or training, such as programming, data analysis, or laboratory testing. Soft skills refer to interpersonal abilities like communication, leadership, adaptability, and teamwork.
Why are professional skills important for careers and resumes?
Professional skills help employers evaluate whether a candidate can perform job responsibilities effectively. Listing relevant skills on a resume demonstrates qualifications and helps applications pass Applicant Tracking Systems used in modern hiring processes.
What professional skills do employers look for?
Employers usually value a combination of technical expertise and transferable workplace skills. Common examples include analytical thinking, communication, teamwork, leadership, time management, adaptability, and digital literacy.
How can professionals develop professional skills?
Professionals can develop skills through continuous learning, training programs, certifications, mentorship, and practical work experience. Staying updated with industry trends also helps individuals maintain relevant and competitive skills.
Editorial Process
Lamwork content is developed through structured review of publicly available job postings and documented hiring trends.
Editorial operations are managed by Thanh Huyen, Managing Editor, with research direction and final oversight by Lam Nguyen, Founder & Editorial Lead. Content is periodically reviewed to reflect observable labor market changes.