Engineering, AI, or related field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . More ❯
for efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity More ❯
for efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity More ❯
working with Quant Trading Technology, and/or working with real-time Low Latency Market Data . Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯
working with Quant Trading Technology, and/or working with real-time Low Latency Market Data . Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯
Front Office FX business and products (spot, forwards, options). Familiarity with data visualization tools (Altair Panopticon, Power BI, Tableau). Experience with Python and analytical libraries such as Pandas and NumPy. Clear communication, analytical mindset, and problem-solving ability. Education & Experience Master’s degree (or equivalent) in Computer Science , Mathematics , Physics , or Engineering . Proven experience (3–8 years More ❯
system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯
alerting systems. Work closely with DevOps and infrastructure teams to deploy solutions in cloud and on-prem environments. Required Skills & Experience Strong proficiency in Python , including libraries such as Pandas, NumPy, and PySpark. Experience with data engineering tools (e.g., Airflow, Kafka, SQL, Parquet). Solid understanding of commodities markets , trading workflows, and financial instruments. Familiarity with cloud platforms (AWS, Azure More ❯
frontend build tools Strong Linux and Git skills Desirable skills: AWS or cloud platform experience WebSocket and real-time data handling DevOps tooling (Docker, Kubernetes, Ansible) Data science packages (pandas, numpy, matplotlib) Modern C++ knowledge (C++17 and later) Interest in sports betting, financial services or trading platforms Benefits: Working alongside other extremely talented and driven engineers Extremely lucrative salary, bonus More ❯
alignment between technology initiatives and business objectives. Required Qualifications: 6+ years of experience in full stack software development. Proficiency in sever side Python programming. Proficiency in data analysis using Pandas, Numpy, SciPy etc. Experience with object oriented design, distributed systems architecture, performance tuning. Experience with designing and programming relational database such as MySQL, RedShift, Oracle SQL Server, or Postgres. Experience More ❯
OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯
OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯
Manage cloud-based and on-prem setup Requirements: 25 years experience in ML engineering/MLOps roles Strong proficiency in Python and experience with relevant ML libraries/frameworks (pandas, numpy, sklearn, TensorFlow, PyTorch) Strong understanding and experience in implementing end-to-end ML pipelines (data, training, validation, serving) Experience with ML workflow orchestration tools (e.g., Airflow, Prefect, Kubeflow) and More ❯
scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯
scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯
Mentor junior engineers and contribute to engineering best practices Required Skills & Experience: 5+ years of experience building and maintaining data pipelines in production environments Strong Python and SQL skills (Pandas, PySpark, query optimisation) Cloud experience (AWS preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Swissblock Technologies AG
and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data streams More ❯
e.g., using type hints and understanding the limitations of the 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 More ❯
Strong problem-solving skills and attention to detail. Eagerness to learn about trading systems, low-latency development, and financial markets. Experience with data analytics tools or frameworks (Python, SQL, Pandas, etc.) is advantageous but not essential. A degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Why Join Us Work in a dynamic, high-impact More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Oliver Bernard
Strong problem-solving skills and attention to detail. Eagerness to learn about trading systems, low-latency development, and financial markets. Experience with data analytics tools or frameworks (Python, SQL, Pandas, etc.) is advantageous but not essential. A degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Why Join Us Work in a dynamic, high-impact More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Freshminds
machine learning, particularly in recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work More ❯
machine learning, particularly in recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work More ❯
for a seasoned mid-level Software Engineer with up to 6+ years of hands-on Python experience. Familiarity with AWS Serverless and related technologies would be advantageous. Strengths in Pandas, Polars, Pytest, Postgres, and CI/CD is essential. If you're interested in Agile methodologies, and have a curiosity about DDD and Event-Driven architectures, you'd fit right More ❯
for a seasoned mid-level Software Engineer with up to 6+ years of hands-on Python experience. Familiarity with AWS Serverless and related technologies would be advantageous. Strengths in Pandas, Polars, Pytest, Postgres, and CI/CD is essential. If you're interested in Agile methodologies, and have a curiosity about DDD and Event-Driven architectures, you'd fit right More ❯
