versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Ability to scope and effectively deliver projects What we offer Equity options - share in our success More ❯
Experience in front-office roles or collaboration with trading desks Familiarity with financial instruments across asset classes (equities, FX, fixed income, derivatives) Experience with distributed computing frameworks (e.g., Spark, Dask) and cloud-native ML pipelines Exposure to LLMs, graph learning, or other advanced AI methods Strong publication record or open-source contributions in ML or quantitative finance Please apply within More ❯
Experience in front-office roles or collaboration with trading desks Familiarity with financial instruments across asset classes (equities, FX, fixed income, derivatives) Experience with distributed computing frameworks (e.g., Spark, Dask) and cloud-native ML pipelines Exposure to LLMs, graph learning, or other advanced AI methods Strong publication record or open-source contributions in ML or quantitative finance Please apply within More ❯
ML frameworks such as PyTorch, TensorFlow, and JAX. Skilled in using tools like scikit-learn, XGBoost, and LightGBM. Data Engineering & Infrastructure Skills - Comfortable working with big data technologies (Spark, Dask), SQL/NoSQL databases, and cloud platforms (AWS, GCP, Azure). Able to build scalable ML pipelines for large-scale financial data. Model Optimisation & Deployment Experience - Proven track record of More ❯
GFS. Solid grasp of time-series and geospatial data concepts. Familiarity with collaborative software development practices (CI/CD, version control, testing). Bonus: experience with distributed computing (Spark, Dask), container orchestration (Kubernetes, Airflow), and dashboarding/uncertainty quantification. This is a rare chance to build differentiated infrastructure that directly supports alpha generation. You'll work closely with world-class More ❯
GFS. Solid grasp of time-series and geospatial data concepts. Familiarity with collaborative software development practices (CI/CD, version control, testing). Bonus: experience with distributed computing (Spark, Dask), container orchestration (Kubernetes, Airflow), and dashboarding/uncertainty quantification. This is a rare chance to build differentiated infrastructure that directly supports alpha generation. You'll work closely with world-class More ❯
london (city of london), south east england, united kingdom
Selby Jennings
GFS. Solid grasp of time-series and geospatial data concepts. Familiarity with collaborative software development practices (CI/CD, version control, testing). Bonus: experience with distributed computing (Spark, Dask), container orchestration (Kubernetes, Airflow), and dashboarding/uncertainty quantification. This is a rare chance to build differentiated infrastructure that directly supports alpha generation. You'll work closely with world-class More ❯
and streamline ML workflows. Develop tools that make data discoverable, reusable, and reliable throughout the ML lifecycle. You Strong Python skills and experience with distributed systems (Ray, Spark, Flyte, Dask). Hands-on with cloud, Kubernetes, and distributed training (Ray, PyTorch DDP, Horovod). Familiar with dataset versioning and experiment tracking (DVC, MLflow). Bonus Points Experience in simulation, robotics More ❯
Triton, and/or CUDA code to achieve performance breakthroughs. Required Skills Understanding of Linux systems, performance analysis tools, and hardware optimisation techniques Experience with distributed training frameworks (Ray, Dask, PyTorch Lightning, etc.) Expertise with Python and/or C/C++ Development with machine learning frameworks (JAX, Tensorflow, PyTorch etc.) Passion for profiling, identifying bottlenecks, and delivering efficient solutions. More ❯
scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready models. Curiosity, pragmatism, and the mindset to solve problems where milliseconds and More ❯
scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready models. Curiosity, pragmatism, and the mindset to solve problems where milliseconds and More ❯
scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready models. Curiosity, pragmatism, and the mindset to solve problems where milliseconds and More ❯
scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready models. Curiosity, pragmatism, and the mindset to solve problems where milliseconds and More ❯
london (city of london), south east england, united kingdom
Harrington Starr
scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready models. Curiosity, pragmatism, and the mindset to solve problems where milliseconds and More ❯
Job title: Quantitative Developer (C++ or Python) Client: Scientific Quant Fund Salary: £70,000 - £275,000 Base (+ Bonus) Location: London (Hybrid) The role: My client are seeking a talented Quantitative Developer to help build their next generation performance trading More ❯
Robert Half Technology are assisting a rapidly growing hedge fund to recruit a Quantitative Developer on a contract basis A leading hedge fund with a strong track record in systematic and quantitative trading. The firm combines advanced research, technology, and More ❯
