built scalable backend systems and APIs (RESTful/GraphQL), with solid experience in microservices and databases (SQL/NoSQL). You know your way around big data tools (Spark, Dask) and orchestration (Airflow, DBT). You understand NLP and have experience working with Large Language Models. You're cloud-savvy (AWS, GCP, or Azure) and comfortable with containerization (Docker, Kubernetes More ❯
Science, Engineering, or equivalent practical experience Desirable: Experience with LLMs or transformer-based architectures (e.g., OpenAI, Mistral, or custom-trained models) Familiarity with tools such as Airflow, Spark, or Dask for large-scale data processing Awareness of AI ethics, data privacy, and legal considerations in high-stakes environments People Source Consulting Ltd is acting as an Employment Agency in relation More ❯
in data modeling, architecture, and processing unstructured data. Experience with processing 3D geometric data. Experience with large-scale, data-intensive systems in production. Knowledge of distributed computing frameworks (Spark, Dask, Ray). Experience with cloud platforms (AWS, Azure, GCP). Proficiency with Docker, Linux, and bash. Ability to document code, architectures, and experiments. Preferred Qualifications Experience with databases and data More ❯
Out in Science, Technology, Engineering, and Mathematics
governance processes. Requirements: 5+ years of experience in data engineering, with a strong focus on building scalable data platforms. Proficiency in Python and modern data libraries (e.g. Pandas, PySpark, Dask). Strong SQL skills and experience with cloud-native data tools (AWS, GCP, or Azure). Hands-on experience with tools like Airflow, Spark, Kafka, or Snowflake. Experience working with More ❯
Computer Science. Minimum of 4 years of experience in designing, developing and deploying production-level deep learning recommendation models with a proven business impact. Fluency in Python, Pandas/Dask, SQL, PyTorch or Tensorflow. Ability to write readable and maintainable code. Strong communication and storytelling skills with both technical and non-technical audiences. Ability to present complex technical subjects to More ❯
collaborative, and dynamic environment. Nice to haves: Prior experience with PCB design, EDA tools, or related optimization problems. Hands-on experience in high-performance computing environments (e.g., Kubernetes, Ray, Dask). Contributions to open-source projects, publications, or top placements in ML competitions (e.g., Kaggle). Expertise in related fields such as Computer Vision, Representation Learning, or Simulation Environments. Our More ❯
major ML conferences; Experience with one lower level language (not limited to, but such as C++, Rust); Experience with large scale data processing and database tools such as MapReduce, Dask, SQL, Hugging Face Datasets, TileDB, Ray. The salary range for Cambridge, UK: - Senior Machine Learning Engineer: £90,950 - £123,050 Staff Machine Learning Engineer: £113,900 - £154,100 Exact compensation More ❯
decisions in the face of many nuanced trade offs and varied opinions. Experience in a range of tools sets comparable with our own: Database technologies: SQL, Redshift, Postgres, DBT, Dask, airflow etc. AI Feature Development: LangChain, LangSmith, pandas, numpy, sci kit learn, scipy, hugging face, etc. Data visualization tools such as plotly, seaborn, streamlit etc You are Able to chart More ❯
compute resources and the ability to interpret performance metrics (e.g., CPU, memory, threads, file handles). • Knowledge and experience in distributed computing - parallel computation on a single machine like DASK, Distributed processing on Public Cloud. • Knowledge of SDLC and experience in working through entire life cycle of the project from start to end ABOUT GOLDMAN SACHS At Goldman Sachs, we More ❯
