ARTIFICIAL INTELLIGENCE RESEARCHER JOB DESCRIPTION

Artificial Intelligence Researcher means something precise: the disciplined production of novel, deployable knowledge. This is not software development with a research label attached. An AI Researcher owns the full arc from problem formulation through prototype delivery, working across paradigms that include deep learning, reinforcement learning, Explainable AI, and knowledge representation, often under peer-review accountability that few engineering titles carry. Findings ship as both working code and published or client-facing results. The role typically operates within R&D groups where external partnership with academic institutions and industry consortia is part of the mandate, not a side activity.

As the Artificial Intelligence Researcher, you translate unstructured technical and business problems into validated machine learning and deep learning solutions that advance both the organization's research agenda and its applied deliverables. You operate within a specialized R&D function, collaborating with cross-functional scientific teams, client stakeholders, or academic partners depending on the organizational model, with scope that spans individual prototype development through supervision of junior researchers.

Career Impact: Sustained output in this role builds a peer-reviewed publication record and a track record of prototype delivery that carries direct market value across research organizations, enterprise AI teams, and academic institutions.

Business Impact: The solutions you develop shape whether clients and internal stakeholders can act on their most complex data challenges, from enrollment simulations in therapeutic R&D to computer vision systems with production deployment requirements.

Growth Opportunity: Exposure to Explainable AI, reinforcement learning, and cross-disciplinary applied domains positions you to move into Principal Researcher, Research Lead, or applied AI architecture roles where research agenda ownership expands significantly.

• Design and implement deep learning and machine learning solutions addressing defined business or scientific problems across project scope from ideation to delivery.
• Develop prototypes using open-source frameworks, incorporating feedback from end users and field tests to drive production-ready adaptation.
• Conduct research across active paradigms including reinforcement learning, Explainable AI, and knowledge representation, maintaining currency with peer-reviewed literature.
• Partner with internal scientific teams, client stakeholders, and academic collaborators to align research direction with organizational and external priorities.
• Publish and present findings at conferences, workshops, and in technical reports, and serve in peer review or programme committee roles where appropriate.
• Mentor junior researchers and developers, supporting both technical skill development and project execution on scoped deliverables.
• Propose, plan, and execute new research projects, including scoping funding opportunities and defining technical milestones.
• Validate and test models against defined requirements, documenting architectural decisions and communicating results to technical and non-technical audiences.

• Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative discipline, or equivalent research experience.
• 4 or more years of AI research and development experience, with a track record of prototype delivery from concept through tested implementation.
• Demonstrated ability to design, train, and evaluate models using deep learning and machine learning methods across at least one major paradigm.
• Working knowledge of reinforcement learning, natural language processing, or computer vision, with the ability to extend into adjacent research areas independently.
• Experience deploying or integrating AI solutions on cloud infrastructure, with understanding of scalability and computational resource constraints.
• Proven written and verbal communication skills, including the ability to produce technical reports, white papers, or peer-reviewed contributions.
• Ability to manage concurrent project responsibilities independently, with strong organizational and time management practices.

• PhD in Computer Science, Mathematics, or a related discipline, with a thesis or publication record in a recognized AI research area.
• Research experience in Explainable AI, Trustworthy AI, or probabilistic reasoning, including familiarity with knowledge graphs or logic programming frameworks.
• Background working with high-performance computing infrastructure or large-scale distributed training environments.
• Demonstrated involvement in the external research community through conference presentations, grant applications, or academic consortium participation.

• Publication and presentation output rate, measured against agreed research dissemination targets per cycle.
• Prototype delivery rate, tracking the proportion of proposed solutions reaching a tested, demonstrable state within scoped timelines.
• Model performance improvement over baseline, quantified per project by accuracy, F1, or task-specific metrics.
• Stakeholder adoption rate of delivered prototypes, reflecting how often research outputs advance to production evaluation or client deployment.
• Peer review and knowledge-sharing contributions per year, measured by conference committee roles, internal presentations, or co-authored outputs.
• Typical tools: deep learning frameworks (commonly PyTorch or TensorFlow); cloud ML platforms (commonly AWS SageMaker or Azure ML); version control and experiment tracking (commonly Git and MLflow).

• Base Salary Range: $130,000 to $185,000 annually, varying by seniority and domain depth
• Bonus: 8 to 15% annual performance bonus tied to research output and project milestones
• Equity: RSUs or options common at growth-stage and public technology employers
• Health Benefits: Medical, dental, and vision coverage; employer contribution typically 80 to 100%
• PTO: 15 to 20 days annually, plus federal holidays and research conference attendance allowance
• Common Perks: Conference travel and registration budget, continuing education stipend, publication support, and relocation assistance for senior hires

Figures are estimates based on general US market benchmarks and may be outdated. Adjust based on location, company size, and seniority level.

Work authorization in the United States is required; employment is contingent on verified eligibility to work without sponsorship restrictions, where applicable to the role. All qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex, national origin, disability, age, veteran status, or any other characteristic protected under applicable federal, state, or local law. Reasonable accommodations are available to individuals with disabilities throughout the application and employment process upon request. A background check is a condition of employment.

The Artificial Intelligence Researcher owns the design, training, and integration of AI models for enterprise web applications and IT systems. Reporting to engineering leadership and partnering with project managers, the role mentors less experienced engineers while automating business processes and building self-service features that strengthen operational efficiency.

Key Responsibilities

• Design, develop, train, and maintain AI models for web applications.
• Mentor and lead less experienced engineers.
• Coordinate planning and development with project managers.
• Support and enhance key applications and IT systems.
• Automate business processes and build self-service features.
• Research and adapt to emerging technologies.
• Assist in solving technology-related problems.

Required Qualifications

• Bachelor's degree in Computer Science, Management Information Systems, a related technology field, or equivalent experience.
• Master's degree, preferably in a technical field.
• 4+ years of experience developing artificial intelligence.
• Experience in designing, training, and integrating AI solutions into enterprise applications.
• Experience with system architecture, application design, and database design and administration.
• Experience with TensorFlow, ML.NET, PyTorch, OpenNN, and/or Flux.
• Experience with open-source frameworks.
• Experience with Scrum or Kanban agile development methodologies.
• Strong understanding of object-oriented programming, design patterns, and principles.
• In-depth knowledge of Robotic Process Automation, Natural Language Processing, and Machine Learning.
• Strong communication skills and a logical, analytical mindset.
• Willingness to learn new technologies and ability to work independently and multi-task.

Embedded within a cross-disciplinary research organization spanning maritime, oil and gas, power and renewables, and precision medicine, the Artificial Intelligence Researcher produces proofs of concept, demonstrators, and prototypes that shape future service offerings. Working closely with internal and external stakeholders, the researcher writes technical reports and proposes new research projects that create lasting business value.

Key Deliverables

• Identify, explore, and develop new research opportunities to create value for business activities and future strategy.
• Develop cutting-edge AI technologies to enhance current services and shape the future, including delivery of proofs of concept, demonstrators, and prototypes.
• Conduct cross-disciplinary research across multiple areas, including maritime, oil and gas, power and renewables, and precision medicine.
• Write technical reports, publish position papers and white papers, and present results to internal and external stakeholders.
• Propose and plan new research projects.

Education & Experience

• Master's degree or higher in a related discipline or research area, such as AI and Machine Learning, Computer Science and Engineering, Information Science, or Mathematics.
• 3–5 years of experience conducting research and development resulting in creative solutions.
• Familiarity with mainstream machine learning algorithms.
• Familiarity with big data technologies and SCADA systems is a plus.
• Experience in sensor technologies and AIoT is a plus.
• Renewable energy industry experience is a plus.
• Familiarity with AI-related risk is a plus.
• Strong self-motivation, critical thinking, and results-driven approach, with the ability to work independently and as a collaborative team member.
• Good coding and communication skills.

Reporting to internal project leadership, the Artificial Intelligence Researcher delivers advanced Deep Learning and Computer Vision solutions that translate complex business problems into practical machine learning applications. Partnering with academic and industry stakeholders, the researcher communicates findings proactively and stays current on state-of-the-art techniques to support project delivery from ideation to completion.

Core Functions

• Translate complex business problems into Deep Learning and Machine Learning solutions.
• Design, implement, and deliver advanced Deep Learning and Computer Vision solutions to address a wide variety of business problems.
• Build relationships with internal project stakeholders and external partners from academia and industry.
• Communicate proactively to share work and present insights and findings.
• Stay current on state-of-the-art Deep Learning and Computer Vision techniques.

Qualifications & Experience

• Master's degree in Engineering, Computer Science, or a related field.
• PhD in Engineering, Computer Science, or a related field is preferred.
• A publication track record in AI venues is a plus.
• Proven experience building Deep Learning and Computer Vision solutions with PyTorch or TensorFlow.
• Experience building and deploying Deep Learning solutions on cloud platforms such as Microsoft Azure and AWS.
• Hands-on experience with self-supervised learning is preferred.
• Experience across the project lifecycle from ideation to delivery, with a track record of project delivery, is a plus.
• Excellent communication skills and experience working in fast-paced environments and project teams.

Sitting at the intersection of data science and therapeutic research, the Artificial Intelligence Researcher contributes to patient modeling and enrollment simulations that accelerate global drug development. Operating across cross-functional scientific and data science teams, the researcher tests and adjusts code to deliver scalable machine learning solutions that impact R&D functions and therapeutic areas.

Core Responsibilities

• Test code and adjust it according to requirements.
• Contribute to projects and collaborate with research scientists across diverse projects.
• Provide scalable machine learning solutions and observations to impact R&D functions and therapeutic areas.
• Participate in cross-functional collaborative efforts with internal scientific and data science teams.
• Lead and contribute to the development of machine learning and AI solutions to accelerate global development.
• Contribute to patient modeling and enrollment simulations.

Background & Experience

• Bachelor's or Master's degree in Engineering, Computer Science, or equivalent experience.
• At least 3 years of relevant experience as an AI scientist.
• Experience in Python and Machine Learning.
• Ability to understand scientific papers.
• Strong listening and communication skills.

A key member of the high-performance computing research practice, the Artificial Intelligence Researcher meets with clients to propose and implement AI solutions centred on deep neural networks. Collaborating across commercial and academic partners, the researcher manages or directs project teams while maintaining a position at the cutting edge of AI theory and practice.

Areas of Ownership

• Meet with clients to understand critical challenges and propose AI solutions, typically centred around deep neural networks.
• Develop project plans to implement proposed AI solutions.
• Implement proposed AI solutions, including using high-performance computing infrastructure to train deep neural networks.
• Make site visits to commercial and academic partners.
• Manage small-scale projects and help direct larger ones (more experienced candidates).
• Expand knowledge of AI techniques to maintain a position at the cutting edge of theory and practice.

Knowledge Skills & Abilities

• PhD or Master's degree in a mathematical, physical, or scientific discipline, or equivalent.
• A PhD in Computer Science, mathematical physics, or a related scientific discipline is preferred.
• Solid background in applied mathematics, preferably in a field based on mathematical analysis such as calculus.
• Knowledge of AI technologies, high-performance computing, and parallel software development.
• Experience managing small to medium-sized projects (more experienced candidates).
• Strong leadership skills with experience leading, motivating, and developing others (more experienced candidates).
• A history of demonstrable excellence in research, such as a strong publication record or a track record of technically cutting-edge projects.
• Excellent verbal and written communication skills.
• Enthusiasm for AI, strong time management, and the ability to deliver against work plans.

Reasoning advances in Trustworthy AI and Meta Learning depend on the Artificial Intelligence Researcher, who researches Statistics, Machine Learning, and Reinforcement Learning at the state of the art. Based within a research organization working with knowledge graphs and logic programming, the researcher applies symbolic AI and probabilistic reasoning to intent specification and human-machine interaction.

Operational Focus

• Research and develop advances in Statistics and Machine Learning, following the state of the art in the chosen field of expertise.
• Research and develop advances in Machine Reasoning and Reinforcement Learning, including recent developments.
• Conduct research in Explainable AI, Trustworthy AI, and Meta Learning.
• Apply understanding of symbolic artificial intelligence and logical and probabilistic reasoning.
• Work with knowledge graphs, knowledge representation, logic programming, and methods and tools for intent specification and human–machine interaction.

Technical Qualifications

• PhD with a thesis in AI planning, multi-objective optimisation, Explainable AI, or Trustworthy AI.
• 5+ years of relevant experience in research organisations or academia.
• Demonstrated ability to develop novel and innovative ideas and generate patents.
• Strong track record of publishing results at conferences and in journals.
• Demonstrated implementation and programming skills, including experience with open-source software stacks.
• Knowledge of application areas such as 5G, cloud computing, IoT, Computer Vision, and Speech Processing is a strong plus.
• Openness and ability to learn new technologies quickly and to work in adjacent areas.

As an Artificial Intelligence Researcher, this role investigates applied industry domains to devise machine learning, NLP, and optimisation solutions for the world's largest firms while mentoring junior developers. The AI research group relies on this work to publish papers at top-tier conferences, build client relationships, and pursue research grants that advance the broader research agenda.

Role Responsibilities

• Investigate applied industry domains to understand client challenges thoroughly.
• Devise new solutions to client challenges by applying expertise in machine learning, NLP, optimisation, and related disciplines.
• Explore and define new research problems within the AI research agenda.
• Implement and execute projects within the AI group.
• Build on ideas from leads and stakeholders to produce high-quality deliverables.
• Build relationships with client teams and serve as a technology expert when working with clients.
• Participate and serve in the research community through conferences, consortiums, workshops, and university relationships.
• Explore and apply for research grants from internal and external funding organisations.
• Pursue research projects in both their conception and technical development.
• Supervise and mentor junior developers to help them complete responsibilities and support career progression.
• Build prototypes from concept through design, coding, and testing, and adapt them based on client needs to drive successful deployment.
• Publish and present research papers at top-tier conferences, workshops, and journals, and serve as a reviewer, technical programme committee member, or panelist.
• Contribute to knowledge exchange, discussion boards, and points of view, and present to internal audiences.

Professional Experience

• 4+ years of experience creating prototypes and testing ideas related to Machine Learning, NLP, and AI.
• 5+ years of technology-related research prototype development.
• Proven ability to create a project plan and execute against it.
• Proven ability to motivate and lead a high-performance, team-oriented environment.
• Strong organisational and time-management skills.
• Excellent communication skills, both written and verbal.

Artificial Intelligence Researcher designs prototype software and delivers practical solutions to complex problems within a small, cutting-edge research and development team. Success in the position means incorporating feedback from end users and field tests while exploring technical possibilities collaboratively with colleagues using the latest open-source machine learning technologies.

Day-to-Day Responsibilities

• Work with a small team on cutting-edge research and development projects.
• Design and develop prototype software using the latest open-source technologies.
• Receive and incorporate feedback from end users, field tests, and exercises.
• Explore technical possibilities collaboratively with motivated colleagues.
• Deliver practical solutions to complex problems.

Minimum Qualifications

• Master's degree in Computer Science with 4+ years of direct experience, or a PhD in Computer Science.
• Strong programming skills and experience with Java and/or C++.
• Experience with machine learning frameworks and analytic tools such as TensorFlow, Torch, and PyTorch, including experience designing, prototyping, training, and evaluating machine learning methods.
• Experience with reinforcement learning techniques is a plus.
• Experience with symbolic or rule-based AI systems is a plus.
• Experience with autonomous robotics platforms, sensors, and actuators is a plus.
• Experience with computer vision, LiDAR, point clouds, and/or photogrammetry techniques is a plus.
• Must be a US person or able to obtain an export authorisation from the appropriate government agency.
• Creative problem-solving ability, passion for software engineering practices, and excellent communication skills.