Jobgether
Senior ML Engineer (AI Research)
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Job Description: Senior ML Engineer (AI Research)
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior ML Engineer (AI Research) based in United Kingdom.
This is a senior-level machine learning engineering role focused on applied AI research and the development of advanced intelligent systems.
You will work on research problems spanning reinforcement learning, agentic systems, reasoning models, web-scale data, and efficient model training.
The role combines rigorous experimentation with strong software engineering and large-scale model development.
You will design and execute research experiments, investigate new approaches, and translate promising findings into practical AI capabilities.
Your work may involve distributed training across multiple compute nodes and modern deep learning frameworks and infrastructure.
You will collaborate with researchers and engineering teams to turn research results into impactful applications and technical contributions.
This is an opportunity to work on challenging AI problems in a fast-moving, international, research-driven environment.
Accountabilities
- Conduct applied machine learning research across areas such as guided search, reinforcement learning, agentic systems, reasoning models, and model distillation.
- Design and execute experiments to identify efficient approaches for training large language models using interaction traces from diverse environments.
- Explore methods for guided generation and search within model trajectory spaces.
- Investigate approaches for collecting and mining relevant training data at web scale.
- Develop efficient methods for incorporating large-scale data into model post-training workflows.
- Experiment with different reinforcement learning configurations in domains where rewards can be verified.
- Explore approaches for training AI agents on tasks where reward signals are difficult or impossible to verify directly.
- Formulate research questions and translate hypotheses into well-designed machine learning experiments.
- Design experiments with appropriate statistical rigor, ensuring results are reliable, interpretable, and reproducible.
- Analyze experimental results and identify meaningful conclusions, limitations, and opportunities for further research.
- Develop and train large-scale machine learning models across multiple computational nodes.
- Implement research ideas using modern deep learning frameworks, primarily Python and JAX.
- Translate promising research findings into practical solutions in collaboration with adjacent engineering and research teams.
- Contribute to technical publications, research reports, and clear documentation of experimental findings.
- Help shape research directions by identifying promising techniques, evaluating alternatives, and communicating results to technical stakeholders.
- Collaborate with engineers and researchers to develop scalable systems for experimentation, training, evaluation, and model improvement.
- Provide technical leadership and mentorship while contributing hands-on engineering expertise to complex AI research initiatives.
- Contribute to engineering practices that support reliable and reproducible research, including testing, version control, and continuous integration.
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Requirements:
- Significant professional experience in machine learning engineering, applied AI research, or a closely related field, at senior or staff level.
- Profound understanding of the theoretical foundations of machine learning and reinforcement learning.
- Deep expertise in modern deep learning for language processing and generation.
- Substantial experience training large-scale models across multiple computational nodes.
- Strong software engineering capabilities, particularly with Python.
- Deep hands-on experience with modern deep learning frameworks, particularly JAX.
- Strong experience designing, executing, and analyzing machine learning experiments with appropriate statistical rigor.
- Ability to formulate meaningful research questions, design experiments to test hypotheses, and derive actionable conclusions from results.
- Strong understanding of experimental methodology, model evaluation, and interpretation of machine learning results.
- Excellent ability to document technical and research findings clearly and contribute to publications or detailed technical reports.
- Strong communication, collaboration, and technical leadership skills.
- Experience with deep reinforcement learning for LLMs, including techniques such as reward modeling, DPO, and PPO, is an advantage.
- Familiarity with important modern LLM concepts and techniques such as RoPE, ZeRO/FSDP, Flash Attention, and quantization is beneficial.
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline; a Master’s degree or PhD is preferred.
- Track record of building and delivering products or technical systems in a dynamic, startup-like environment is a plus.
- Experience engineering complex systems such as large-scale distributed data processing platforms or high-load web services is advantageous.
- Open-source projects demonstrating strong engineering capabilities are a plus.
- Excellent command of English, with strong technical writing, articulation, and communication skills.
- Proficiency with contemporary software engineering practices, including CI/CD, version control, and unit testing.
- Ability to work independently while collaborating effectively with multidisciplinary research and engineering teams.
- Strong curiosity, analytical thinking, and enthusiasm for solving open-ended and technically challenging AI problems.
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Benefits:
- Competitive compensation.
- Career growth and continuous learning opportunities.
- Flexibility and significant ownership in your work.
- Collaborative and innovative research and engineering culture.
- Opportunity to work on impactful AI research and development projects.
- Exposure to advanced machine learning, reinforcement learning, LLMs, and agentic AI systems.
- Opportunity to contribute to research that can be translated into practical AI applications.
- International environment with talented research and engineering teams.
- Inclusive workplace committed to equal employment opportunities.
- Workplace accommodations available during the application process where required.
- Employment is subject to authorization to work in the country where the position is based.
How Jobgether Works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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