Machine Learning Engineer - Prototyping
Posted 7 days ago by Jobserve
Negotiable
Undetermined
Hybrid
London (Hybrid 3 days)
Summary: The Machine Learning Engineer - Prototyping role focuses on leveraging Python for machine learning prototyping, data processing, and automation. The position requires building end-to-end Proof of Concepts (PoCs) and translating business ideas into technical solutions swiftly. Candidates should possess strong data engineering skills and a practical mindset aimed at delivering business outcomes. The role demands effective communication and the ability to work independently in dynamic environments.
Key Responsibilities:
- Develop and prototype machine learning solutions using Python.
- Build end-to-end Proof of Concepts (PoCs) and rapid prototypes.
- Translate ambiguous business ideas into technical solutions.
- Implement data engineering skills including APIs, data pipelines, and SQL.
- Develop lightweight applications such as APIs, dashboards, and notebooks.
- Deliver PoCs within short timelines and scale them into prototypes.
- Iterate quickly based on stakeholder feedback.
- Communicate findings and feasibility outcomes clearly.
- Work across the full life cycle: data ingestion, modeling, and prototype delivery.
Key Skills:
- Strong hands-on experience with Python for ML prototyping.
- Experience with data processing and automation.
- Strong data engineering skills including APIs and data pipelines.
- Good understanding of machine learning and statistical fundamentals.
- Ability to work independently in fast-paced environments.
- Strong problem-solving and analytical thinking skills.
- Effective communication skills.
- Experience delivering PoCs within short timelines.
- Practical mindset focused on business outcomes.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Strong hands-on experience with Python for ML prototyping, data processing, and automation.
Experience building end-to-end Proof of Concepts (PoCs) and rapid prototypes.
Ability to translate ambiguous business ideas into working technical solutions quickly.
Strong data engineering skills including APIs, data pipelines, SQL, and cloud-based data handling.
Experience developing lightweight applications such as APIs, dashboards, notebooks, or simple frontends.
Good understanding of machine learning and statistical/mathematical fundamentals.
Experience working independently in fast-paced and rapidly changing environments.
Strong problem-solving, analytical thinking, and experimentation mindset.
Ability to iterate quickly based on stakeholder feedback.
Strong communication skills with the ability to clearly present findings and feasibility outcomes.
Experience delivering PoCs within short timelines (2-3 days) and scaling them into prototypes within 2-3 weeks.
Practical mindset focused on business outcomes rather than perfect production-grade code.
Experience working across the full life cycle: data ingestion - modelling - prototype delivery.