AI/ML Engineer building data science and AI solutions for Pharma and MedTech clients on Azure. Collaborating with teams to deliver end - to - end machine learning projects.
About the role
- Senior Machine Learning Engineer developing dataset strategies and model enhancements in a top-tier Quantum Software firm. Collaborating with a multicultural team to innovate in the AI domain.
Responsibilities
- Design and implement strategies for creating, sourcing, and augmenting datasets tailored for LLM training and fine-tuning.
- Develop scalable pipelines to collect, clean, filter, annotate, and validate large volumes of text data, ensuring quality, ethical compliance, etc.
- Collaborate with ML engineers, researchers, and software engineers to achieve ambitious goals in the preparation of LLMs and complementary work (preparing datasets, model evaluation, model serving, etc.).
- Develop and integrate new routines for modifying and enhancing LLMs, and extending their functionality.
- Make effective use of distributed compute resources and clusters (GPU’s), identify opportunities for further optimization.
- End-to-end preparation of compressed and specialized LLMs for use in production.
- Keep up to date with research trends in LLM foundation models, dataset curation, LLM pretraining data, and benchmarking.
- Contribute to building documentation, development standards, and a healthy shared code base.
- Mentor other engineers and provide knowledge sharing of cutting-edge techniques.
Requirements
- Master’s, or Ph.D. in Computer Science, AI, Data Science, Physics, Math, or a related field. Or equivalent industry experience.
- 4+ years of experience in data science, machine learning, or related roles, with demonstrated experience with NLP or LLMs.
- In-depth knowledge of large foundational model architectures (language and multimodal models) and their lifecycle: training, fine-tuning, alignment, and evaluation.
- Proficient in Python and data tooling ecosystems (Pandas, NumPy, Hugging Face Datasets & Transformers libraries).
- Hands-on experience with text data collection from diverse sources: web scraping, APIs, proprietary corpora, etc.
- Strong understanding of data quality metrics including bias detection, toxicity, and readability.
- Experience working in large shared distributed computing environments, familiarity with relevant tools for hardware optimization (vLLM, TensorRT, NeMo, etc.).
- Experience with version control (git), unit testing, and other fundamental aspects of software development.
- Effective communication and interpersonal abilities.
Benefits
- Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion.
- Relocation package (if applicable).
- Up to 9-month contract, ending on June 2026.
- Hybrid role and flexible working hours.
- Be part of a fast-scaling Series B company at the forefront of deep tech.
- Equal pay guaranteed.
- International exposure in a multicultural, cutting-edge environment.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
ML Engineering Lead at Saris AI tackling multi - modal AI systems in banking. Drive technical direction and build high - performing teams in an early - stage startup environment.
Machine Learning Engineer designing and training lightweight ASR models for mobile devices at Plaud. Contributing to optimization, multilingual data management, and deployment collaboration.
Machine Learning Engineer designing post - processing test suites for AI interaction systems at Plaud Inc. Collaborating on speech algorithm training and user experience optimization in San Francisco.
Senior MLOps Engineer deploying ML - powered applications at Allica Bank. Building, prototyping, and ensuring the reliability of AI tools for SMEs.
Intermediate AI/ML Engineer designing and deploying machine learning solutions for video security. Join Solink to transform video security into real - time operational insights in a hybrid work environment.
Senior Machine Learning Engineer for Toyota Connected developing state - of - the - art solutions for in - vehicle Voice Assistants. Collaborating with teams and mentoring junior members to drive innovation in machine learning technology.
MLOps Engineer leading large - scale model deployments and managing CI/CD pipelines in GCP ecosystem. Focus on operational excellence and implementing observability frameworks for AI systems.
Senior Machine Learning Engineer designing AI systems for multi - scale physical technologies at Orbital. Leading high - risk projects with a focus on AI research and engineering excellence.
Machine Learning Engineer at Auror, using data science to reduce retail crime through innovative ML systems. Collaborate with product teams and develop impactful solutions leveraging real - time data.