Enigma

About the Company

Here at Enigma, we specialize in Generative AI recruitment, specifically focused on Machine Learning and Software Engineering disciplines. With a combined experience of 20+ years, we understand the intricacies of finding the perfect role as well as the right talent for your team.

But what sets Enigma apart? Our consultative approach. We don't just match candidates with job openings; we guide candidates, founders, and hiring managers through the recruitment process. Our value-added services go beyond traditional recruitment efforts, offering services such as recruitment process structuring, salary benchmarking, share allocation, CV reviews and so much more.

We're more than recruiters – we're partners in your success journey. Our mission is not only to connect you with exceptional talent and companies but also to support your growth and success every step of the way. We're committed to your success. Let us partner with you to connect you with people and companies alike, that will drive growth and innovation for years to come.

Listed Jobs

Company Name

Enigma

Job Title

Data Scientist | Python | Machine Learning | SQL | Large Language Models | Hybrid, London

Job Description

**Job Title:** Research Data Scientist **Role Summary:** Design, prototype, and deploy data‑driven ML and LLM solutions that transform fragmented industry data into actionable insights, driving product impact for underserved blue‑collar businesses. **Expectations:** - 2+ years of applied data science or ML research experience. - Strong background in quantitative analysis (B.Sc./M.Sc./Ph.D. in statistics, CS, math, or related field). - Proven ability to design, run, and rigorously evaluate experiments with appropriate baselines, controls, and metrics. - Comfortable moving quickly from proof‑of‑concept to production in a fast‑moving environment. - Openness to learn new domains; domain expertise not required. **Key Responsibilities:** - Extract and clean legacy data into structured, usable formats. - Design, execute, and statistically evaluate experiments to test hypotheses. - Prototype ML models for forecasting, optimization, and recommendation across sales, inventory, and operations. - Fine‑tune and apply large language models for practical industry workflows. - Collaborate with engineering teams to transition research outputs into scalable production systems. - Lead a culture of experimentation: document results, share learnings, and influence product strategy. **Required Skills:** - Proficiency in Python and core data science libraries (pandas, NumPy, scikit‑learn, XGBoost). - Experience with deep learning frameworks (PyTorch, Hugging Face). - Strong statistical reasoning and experiment design expertise. - Ability to define evaluation metrics and interpret performance. **Nice‑to‑have Skills:** - LLM fine‑tuning and prompt engineering. - SQL/PostgreSQL data querying. **Required Education & Certifications:** - Bachelor’s, Master’s, or Ph.D. in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Engineering).

London, United kingdom

Hybrid

Junior

04-11-2025

Company Name

Enigma

Job Title

Machine Learning Engineering Manager | Computer Vision | Deep Learning | Python | C++ | London, Hybrid

Job Description

**Job Title** Machine Learning Engineering Manager – Computer Vision & Deep Learning **Role Summary** Lead a multidisciplinary team (5‑10 members) of engineers and applied scientists to design, build, and deploy scalable computer‑vision and deep‑learning solutions for sports and fan engagement. Own end‑to‑end delivery from architecture to production monitoring, ensuring high‑impact outcomes, tight product collaboration, and continuous technical and personal growth for the team. **Expactations** - **Team Leadership** – Manage day‑to‑day operations, set clear goals, and foster a high‑performance culture. - **Technical Ownership** – Define architecture, code standards, and system health across production AI pipelines. - **Cross‑Functional Collaboration** – Work closely with product, engineering, and ops teams to deliver iterative, quality features. - **Talent Development** – Mentor and coach applied scientists and engineers, expanding technical and leadership skill sets. - **Strategic Impact** – Translate business needs into technical solutions that scale and deliver measurable user value. **Key Responsibilities** - Drive team progress toward quarterly and annual targets while maintaining high impact on users and business KPIs. - Lead architectural decisions; ensure code quality, scalability, and cost‑efficiency of AI/ML systems. - Coordinate cross‑team dependencies, facilitate iterative releases, and uphold product quality. - Build and optimize technical processes and team structure for reliable delivery. - Provide career mentorship for applied scientists and engineers. - Maintain production readiness: deployment, monitoring, scaling, and reliability of large‑scale AI workloads. **Required Skills** - Proven leadership with 5‑10 technical contributors. - Hands‑on experience building, operating, and monitoring production AI/ML systems. - Strong proficiency in: - Classical & deep learning computer vision - Multi‑view geometry - GPU‑accelerated computing / Edge inference - Real‑time systems / Signal processing - Large language models (LLMs) (preferred) - Excellent communication; able to explain complex concepts to technical and non‑technical stakeholders. - Product‑oriented mindset with a track record of delivering AI‑driven features. **Required Education & Certifications** - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field. - (Optional) Technical certifications in cloud AI/ML platforms, GPU programming, or related domains.

United kingdom

Remote

10-11-2025

Company Name

Enigma

Job Title

Research Scientist | Diffusion Modelling | Python | PyTorch | Machine Learning | Generative Modelling | Hybrid, London

Job Description

Job Title: Research Scientist | Diffusion Modelling | Python | PyTorch | Machine Learning | Generative Modelling | Hybrid Role Summary: Develop and deploy diffusion‑based generative models for functional protein design, collaborating with interdisciplinary ML, biology, and engineering teams to translate models into laboratory‑validated therapeutics. Expactations: - Extensive research experience in generative modeling (e.g., diffusion, VAEs, GANs). - Proven ability to engineer production‑grade ML systems and rapid prototypes. - Expertise in building scalable data pipelines and training large‑scale models on cloud or distributed platforms. - Strong focus on model quality, performance, and end‑to‑end optimization. - Adaptability to fast‑moving, mission‑driven environments and cross‑functional collaboration. Key Responsibilities: - Curate and preprocess training/evaluation datasets for protein modeling. - Define and implement practical evaluation metrics aligned with biological objectives. - Rapidly prototype and iterate generative modeling approaches (e.g., diffusion models). - Collaborate on shared codebase with researchers and engineers. - Support compute infrastructure, experimentation tracking, and model development pipelines. - Liaise with experimentalists to plan lab testing and deploy model inference on biological targets. - Integrate laboratory feedback to refine models and datasets. - Stay current on advances in ML and protein science; share knowledge internally. Required Skills: - Python programming; deep learning frameworks (PyTorch, TensorFlow). - Generative modeling (diffusion models, VAEs, GANs). - Large‑scale model training, distributed computing, cloud platforms (AWS, GCP, Azure). - Data engineering: pipeline construction, data inspection, dataset splitting, performance monitoring. - Software engineering best practices (unit testing, CI/CD, version control). - Strong analytical skills, model optimization, and throughput tuning. - Effective communication across technical and biological disciplines. Required Education & Certifications: - Ph.D. or advanced master’s degree in Computer Science, Machine Learning, Computational Biology, Bioinformatics, or related field. - Demonstrated publication record or significant contributions to open‑source ML libraries. - Relevant certifications in cloud technologies or deep learning are a plus.

London, United kingdom

Hybrid

24-11-2025

Company Name

Enigma

Job Title

AI Research Scientist | Machine Learning | Deep Learning | Natural Language Processing | LLM | Hybrid | San Jose, CA

Job Description

Job Title: AI Research Scientist Role Summary: Lead advanced research in machine learning, deep learning, and natural language processing to design, evaluate, and deploy AI solutions that meet production needs. Expectations: Deliver research-driven innovations, design rigorous experimental protocols, and bridge the gap between cutting‑edge research and scalable production systems. Key Responsibilities: - Design, execute, and analyze ML experiments; establish baselines and select evaluation metrics. - Identify, adapt, and validate novel AI techniques for company use cases. - Define rigorous evaluation protocols (offline metrics, user studies, adversarial testing) for statistical soundness. - Specify data and annotation requirements; develop guidelines and oversee quality control. - Collaborate with domain experts, product managers, and engineering to refine problem statements and operational constraints. - Create reusable research assets (datasets, modular code, evaluation suites, documentation). - Work with ML Engineers to optimize training and inference pipelines for production integration. - Contribute to academic publications and represent the organization in research communities. Required Skills: - Strong foundation in ML and DL algorithms; proficiency with PyTorch, Hugging Face, NumPy. - Hands‑on experience with PEFT/LoRA, adapters, fine‑tuning, RLHF/RLAIF (PPO, DPO, GRPO). - Expertise in hypothesis‑driven experimentation, ablation studies, and statistically sound evaluation. - Advanced programming in Python (preferred); experience in C++ or Java. - Solid mathematical foundations in probability, linear algebra, and calculus. - Domain expertise in NLP, symbolic reasoning, or speech processing. Required Education & Certifications: - Ph.D. in Computer Science, AI, ML, or related field preferred; Master’s with exceptional research or industry experience acceptable. - 3–5 years of AI/ML research experience in applied or product environments, with a track record of production deployments. - Publications in top‑tier AI/ML conferences (e.g., NeurIPS, ICML, ACL, CVPR) preferred.

San jose, United states

Hybrid

Junior

26-11-2025