Machine Learning Engineer
Posted 1 week ago by Sanderson
£750 Per day
Inside
Remote
London Area, United Kingdom
Summary: The role of Machine Learning Engineer involves joining a FTSE 100 retail client's data science function to implement advanced machine learning technologies. The position requires expertise in timeseries forecasting and a strong background in data science and machine learning. The role is fully remote and is expected to last for an initial period of six months. Candidates must possess significant experience with Python and relevant machine learning libraries.
Key Responsibilities:
- Drive cutting-edge machine learning technology across the business.
- Develop and implement timeseries forecasting models.
- Utilize Python and machine learning libraries for data analysis and model development.
- Collaborate with the data science team to enhance machine learning services.
- Apply knowledge of machine learning algorithms and computer science fundamentals.
Key Skills:
- Significant experience as a Data Scientist/Machine Learning Engineer.
- Extensive experience with Python and libraries (e.g., NumPy).
- Desirable experience with GCP and VertexAI.
- Strong understanding of timeseries forecasting.
- Solid knowledge of machine learning algorithms and modern deep learning techniques.
Salary (Rate): £750 daily
City: London Area
Country: United Kingdom
Working Arrangements: remote
IR35 Status: inside IR35
Seniority Level: Mid-Level
Industry: IT
Machine Learning Engineer £700-750/day overall assignment rate to umbrella Fully remote 6 month initial A FTSE 100 retail client are on the look for a Machine Learning Engineer to join their data science function to drive cutting-edge ML technology across the business. MUST have previous experience of Timeseries forecasting. Machine Learning Engineer, key skills: Significant experience working as a Data Scientist/Machine Learning Engineer Extensive experience with Python and libraries (NumPy etc) GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.)