ML Ops Engineer

TN United Kingdom; London; Hybrid; GBP 60,000 - 100,000; Full time

Job summary

An innovative firm is seeking an experienced ML Ops Consultant to enhance AI/ML processes and insights. This role involves deploying and maintaining AI/ML models, ensuring their reproducibility, and utilizing advanced analytics techniques. The ideal candidate will have extensive Python experience and familiarity with MLOps tools. Join a dynamic team that values collaboration and continuous learning in a hybrid work environment, where your contributions will drive efficiency and innovation in AI/ML solutions. If you're passionate about transforming data into actionable insights, this opportunity is for you.

Qualifications

• 5+ years of hands-on experience in AI/ML focusing on deployment.
• Proficient in Python and familiar with various ML libraries.
• Experience with MLOps tools and cloud providers.

Responsibilities

• Deploy and maintain AI/ML models and services in production.
• Ensure ML models are reproducible and interpretable.
• Monitor and maintain AI/ML services post-deployment.

Skills

Python

AI/ML/Advanced Analytics

MLOps

Data Validation

Communication Skills

Education

University degree in software engineering

5+ years of experience with Python

2+ years of experience with DevOps/CI/CD

Tools

pandas

scikit-learn

xgboost

Azure ML Studio

Git

Job description

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Duration: 1 year contract

Hybrid working: You will be needed onsite in Brussels for team meetings and workshops

We are currently looking for an experienced ML Ops Consultant to join the team on a freelance contract.

As a competency centre for AI/ML, the team helps improve process efficiency and generate insights using techniques such as predictive modelling, natural language processing, GenAI and mathematical optimization.

Qualifications

• You have a proven track record of hands-on experience in AI/ML/Advanced Analytics, focusing on deploying and maintaining AI/ML models and services in production.
• You know how to ensure ML models are reproducible and interpretable.
• You have independently packaged and deployed AI/ML services to production.
• You know how to monitor and maintain AI/ML services post-deployment.
• You are proficient in Python with 5+ years of experience, including libraries like pandas, scikit-learn, xgboost.
• Nice-to-haves include experience with data processing libraries (pydantic, pandera), web frameworks (FastAPI, Flask), MLOps tools (MLFlow, Azure ML Studio), version control (DVC), monitoring solutions (NannyML, Evidently AI), distributed processing frameworks (Ray, Dask, PySpark), pipeline orchestration (Metaflow, ZenML, Kedro, Airflow, Dagster), and more.
• You can write both object-oriented and functional code, understand concepts like (de)coupling, inheritance, and composition.
• You ensure code quality through thorough testing (unit, integration, end-to-end, stress/performance).
• You love data validation and use type hints regularly.
• You can transform messy Jupyter notebooks into production-grade code.
• You know how to package Python applications or libraries for distribution.
• You are a proficient GIT user, following best practices for collaboration.
• You have a good understanding of machine learning algorithms, especially in NLP.
• You have experience with at least one Cloud Provider, preferably Azure.
• You are familiar with Unix/Linux command line tools and scripting (shell, bash).
• Experience with data engineering, SQL, Hadoop ecosystem (Spark, Kafka, Hive, Impala), and Cloudera is a plus.
• You understand the MLOps framework and its integration with DevOps, and can identify gaps for modernization.

Non-technical skills

• You have strong communication skills to present complex concepts to diverse audiences.
• You have experience working in large, complex enterprises and are adaptable to legacy technology.
• You stay updated with new tools and technologies.
• You are a team player and can estimate effort accurately.
• You are familiar with Agile methodologies.
• You promote and advocate for MLOps across organizations.
• You enjoy mentoring and knowledge sharing.

Location requirement:

Candidates must be based in Belgium, France, The Netherlands, or the UK (IR35 check needed).

Formal qualifications:

• University degree in software engineering, Data Science, Machine Learning, Data Engineering, or a related field, with strong IT skills.
• 5+ years of experience with Python.
• 2+ years of experience with DevOps/CI/CD practices.
• 2+ years of experience deploying AI solutions to production.

Please send an up-to-date CV to us.