language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modeling workflows. ML Ops & deployment More ❯
language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modeling workflows. ML Ops & deployment More ❯
customer-facing communication across scientific and engineering audiences. Experience in pharma, biotech, medtech, or healthcare environments (ideal). MSc in Computer Science or equivalent experience. Bonus Familiarity with PyTorch, JAX, Hugging Face, and AWS ML services. Experience optimizing models for low-latency inference. Open-source contributions and/or startup experience. Why This Is Unique Globally competitive salary + More ❯
customer-facing communication across scientific and engineering audiences. Experience in pharma, biotech, medtech, or healthcare environments (ideal). MSc in Computer Science or equivalent experience. Bonus Familiarity with PyTorch, JAX, Hugging Face, and AWS ML services. Experience optimizing models for low-latency inference. Open-source contributions and/or startup experience. Why This Is Unique Globally competitive salary + More ❯
expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modelling workflows. Model development & deployment More ❯
expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modelling workflows. Model development & deployment More ❯
Reinforcement Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this More ❯
City of London, London, United Kingdom Hybrid/Remote Options
microTECH Global LTD
Reinforcement Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this More ❯
Collaborate cross-functionally with hardware, software and research teams. Requirements Strong background in machine learning algorithm development and optimisation. Proficiency in Python and modern ML frameworks such as PyTorch, JAX or TensorFlow. Experience with data modelling, preprocessing and performance benchmarking. Understanding of ML evaluation metrics and model analysis methods. Excellent communication skills and collaborative mindset. 3+ years’ experience in More ❯
Collaborate cross-functionally with hardware, software and research teams. Requirements Strong background in machine learning algorithm development and optimisation. Proficiency in Python and modern ML frameworks such as PyTorch, JAX or TensorFlow. Experience with data modelling, preprocessing and performance benchmarking. Understanding of ML evaluation metrics and model analysis methods. Excellent communication skills and collaborative mindset. 3+ years’ experience in More ❯
Engineering or related quantitative fields. Background in wireless communication systems, e.g., OFDM and MIMO technologies. Track record of related publications or successful projects. Proficiency in Deep Learning frameworks (PyTorch, JAX). Familiarity with advanced AI methods (e.g., transformer models). Excellent scientific communication and teamwork skills. Enthusiasm for innovative research with real-world impact. Join us to shape the More ❯
Engineering or related quantitative fields. Background in wireless communication systems, e.g., OFDM and MIMO technologies. Track record of related publications or successful projects. Proficiency in Deep Learning frameworks (PyTorch, JAX). Familiarity with advanced AI methods (e.g., transformer models). Excellent scientific communication and teamwork skills. Enthusiasm for innovative research with real-world impact. Join us to shape the More ❯
VLMs, or image/video generative models — architecture, training, and inference. Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies. Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. You document experiments clearly and communicate trade‐offs crisply. Nice-to-Have: Robotics or autonomous driving experience. RL for More ❯
VLMs, or image/video generative models — architecture, training, and inference. Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies. Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. You document experiments clearly and communicate trade‐offs crisply. Nice-to-Have: Robotics or autonomous driving experience. RL for More ❯
team at a company 8 months ahead of roadmap What they’re looking for: 3–6 years’ experience writing production-grade code Strong foundation in machine learning (PyTorch/JAX/TensorFlow) Deep understanding of LLMs and RAG, not just LangChain wrappers Bonus: Research internships, papers, or early-stage AI product builds Someone who wants to build real things More ❯
team at a company 8 months ahead of roadmap What they’re looking for: 3–6 years’ experience writing production-grade code Strong foundation in machine learning (PyTorch/JAX/TensorFlow) Deep understanding of LLMs and RAG, not just LangChain wrappers Bonus: Research internships, papers, or early-stage AI product builds Someone who wants to build real things More ❯
Experience 5+ years’ experience in machine learning with a focus on training and inference systems Strong programming expertise in Python and C++ or CUDA Proficiency with PyTorch, TensorFlow or JAX Hands-on experience with GPU acceleration and distributed training (Horovod, NCCL or similar) Background in real-time, low-latency ML pipelines Familiarity with cloud and orchestration technologies Contributions to More ❯
Experience 5+ years’ experience in machine learning with a focus on training and inference systems Strong programming expertise in Python and C++ or CUDA Proficiency with PyTorch, TensorFlow or JAX Hands-on experience with GPU acceleration and distributed training (Horovod, NCCL or similar) Background in real-time, low-latency ML pipelines Familiarity with cloud and orchestration technologies Contributions to More ❯
also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter notebooks Exposure to machine learning libraries like PyTorch, XGBoost and JAX Understanding of crypto or traditional financial markets Strong API design and documentation skills What do you get in return? Up to 250k base (depending on experience) 3 days in More ❯
Central London, London, England, United Kingdom Hybrid/Remote Options
Opus Recruitment Solutions Ltd
also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter notebooks Exposure to machine learning libraries like PyTorch, XGBoost and JAX Understanding of crypto or traditional financial markets Strong API design and documentation skills What do you get in return? Up to £250k base (depending on experience) 3 days in More ❯
at the forefront of innovation. With strategic offices in major cities worldwide, including London, Paris, Berlin, Tunis, Kigali, Cape Town, Boston, and San Francisco, InstaDeep collaborates with giants like Google DeepMind and prestigious educational institutions like MIT, Stanford, Oxford, UCL, and Imperial College London. We are a Google Cloud Partner and a select NVIDIA Elite Service Delivery Partner. … of high-quality research, evidenced by publications in reputable scientific journals or conferences. Expertise in software development and programming in Python. Experience with deep learning frameworks such as PyTorch, JAX, and/or TensorFlow. Excellent ability to communicate complex ideas clearly, both verbally and in writing, and to work effectively within a multidisciplinary team. Strong analytical and critical thinking More ❯
At UnlikelyAI, we're looking for a Senior Applied Scientist to join our Applied Science team. This is a high-impact individual contributor position. You'll help drive the end-to-end lifecycle of projects: from identifying opportunities in literature More ❯
SR2 | Socially Responsible Recruitment | Certified B Corporation™
institutional VCs and prominent angel investors, giving them a solid two-year runway and plans for another upcoming raise. The founding team includes senior engineers and researchers from Meta, Google, and AWS , each with deep experience training and deploying large-scale models. Their mission is simple but ambitious: to develop the next generation of language and multimodal foundation models … data curation, versioning, and reproducible experimentation. You’ll Bring Strong experience with LLMs, generative, or multimodal models , ideally involving large-scale training or evaluation. Hands-on fluency in PyTorch, JAX, or TensorFlow , with experience in DeepSpeed, Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO More ❯
