desire to work with other software engineers. - A passion for learning new skills, including financial concepts and trading workflows. Candidate background - Python development, including: - Scientific libraries (eg, Pandas, Polars, NumPy, SciPy). - Web technologies (eg, Flask, FastAPI). - Data engineering experience. - Familiarity with cloud infrastructure (eg, AWS). Nice-to-Have - JavaScript UI frameworks (eg, React, Vue, Angular). - Docker More ❯
record of scientific software development, including data acquisition and/or data analysis. (S&I) Experience developing well-designed, robust software in Python and its scientific packages (such as numpy, scipy, matplotlib, pandas). (S&I) Understanding of modern software development practices (e.g. testing, version control, continuous integration, Agile, object-oriented design). (S&I) Experience of leading software projects More ❯
Milton Keynes, Buckinghamshire, South East, United Kingdom Hybrid / WFH Options
LA International Computer Consultants Ltd
of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Key Skills & Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline orchestration … Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Writing clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random forests), clustering More ❯
Deployment: ship a model as a container, update an Airflow (or Azure Data Factory) job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow)SQL (Redshift, Snowflake or similar)AWS SageMaker Azure ML migration, with Docker, Git, Terraform, Airflow/ADFOptional extras: Spark, Databricks, Kubernetes. What you'll bring More ❯
