ML OPS Enigneer with data science experience - inside IR35
Posted 1 week ago by Intuition IT Solutions Ltd
Negotiable
Inside
Hybrid
London, Stratford, UK
Summary: The role of ML Ops Engineer/Data Scientist involves deploying and maintaining AI/ML models using AWS SageMaker, with a requirement for on-site presence in London Stratford 40% of the month. The position demands strong collaboration skills and the ability to communicate technical concepts effectively. The candidate should have a solid background in data science, DevOps, and experience with microservices and REST APIs. This is a contract role classified as inside IR35, with an immediate start date.
Key Responsibilities:
- ML Ops engineer with experience in data science, DevOps, and AWS SageMaker for model deployment (ML life cycle).
- Travel to London Stratford client office 40% a month (travel allowance not included).
- Excellent soft skills, Sr. Consultant with hands-on experience.
Key Skills:
- Demonstrated experience deploying and maintaining AI/ML models in production environment using AWS SageMaker.
- Hands-on experience with AWS Machine Learning and Data services: SageMaker, Bedrock, Glue, Kendra and ECS Fargate.
- Ability to develop and host microservices and REST APIs using Flask, FastAPI, or equivalent frameworks.
- Proficiency with SQL, version control (Git), and working with Jupyter or RStudio environments.
- Strong cross-functional collaboration skills and the ability to explain technical concepts to nontechnical stakeholders.
Salary (Rate): £450.00/day
City: London
Country: UK
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
ROLE: ML OPS Engineer/Data scientist
Location: London Stratford 40% a month on site
Rate: 450.00£/day inside IR35
Start date: ASAP
Key requirement:
- ML Ops engineer with experience in data science, DevOps, and AWS SageMaker for model deployment (ML life cycle).
- Travel to London Stratford client office 40% a month (travel allowance not included).
- Excellent soft skills, Sr. Consultant with hands-on experience.
Essential skills:
Demonstrated experience deploying and maintaining AI/ML models in production environment using AWS SageMaker.
Hands-on experience with AWS Machine Learning and Data services: SageMaker, Bedrock, Glue, Kendra and ECS Fargate.
Ability to develop and host microservices and REST APIs using Flask, FastAPI, or equivalent frameworks.
Proficiency with SQL, version control (Git), and working with Jupyter or RStudio environments.
Strong cross-functional collaboration skills and the ability to explain technical concepts to nontechnical stakeholders.