Snr Machine Learning Engineer (AI/ML/EDA, Models, Deployment)

Senior Machine Learning Engineer (AI/ML/EDA, Models, Deployment) – Banking Client – Brussels

Rate: €700 – €900 per day

Duration: 6 months

Remote Working Available (4 days onsite in a month only)

Data Analytics & AI chapter supports the Data Science needs of all the Group entities. As a competency centre for analytics, the team helps improve process efficiency and generate insights using techniques such as predictive modelling, natural language processing, process mining and network analytics.

Qualifications

• You have a proven track record of hands-on experience in the area of AI/ML/Advanced Analytics, with special focus on deploying and maintaining Machine Learning models in production.
• Keywords: EDA, model selection, tuning, evaluation, serving.
• Bonus for: NLP, OCR and text classification.
• You make sure the models you build and deploy are reproducible and interpretable.
• You have already single-handedly packaged and deployed models to production.
• You know how to monitor and update AI models post-deployment.
• You are proficient in Python
• You have 5+ years of work experience with Python, and AI/ML standard libraries such as pandas, scikit-learn, xgboost
• Nice-to-haves: FastAPI, PySpark, pydantic, pandera, NannyML, MLFlow, dagster, Airflow
• You can write OO code and understand concepts such as (de)coupling, coherence, inheritance, composition.
• You love and regularly use data validation, type hints, pytest, coverage, tox, mypy, black, flake8.
• You know how to turn a messy jupyter notebook into a production-grade piece of code.
• You know how to package a python application or library for distribution
• You are a proficient GIT user, able to collaborate with multiple developers on multiple repositories, while following best practices related to branching, merging and code reviews.
• You have experience with Unix/Linux command line tools and scripting (shell, bash):
• VIP club membership if you have at least once ran `rm -rf` on production data.
• You possess the foundational Data Engineering skills, allowing you to interact with the Data Engineering team, and analyze and troubleshoot data pipelines if needed:
• You are comfortable with using SQL to extract, transform and load data (ETL/ELT).
• Experience with the Hadoop ecosystem (Spark, Kafka, Hive, Impala…) is a plus.
• Experience with the Cloudera distribution is an additional plus
• You understand the modern MLOps framework and complexities it adds to DevOps.
• You are able to identify the MLOps maturity gaps and provide inputs for modernization efforts.

Non-technical

• You have strong verbal and written communication skills as well as good customer relationship skills to present complex concepts and/or the results of a use case to different audiences (from end users up to division management).
• You have experience of working in large, complex enterprises and have stoically accepted it as your fate.
• You are not allergic to legacy technology, yet are stubborn and persistent in pushing for modernization.
• You stay up-to-date with new tools, technologies and approaches within the domain.
• You are a well-integrated team player.
• You are able to estimate your short-term effort with reasonable accuracy and get the work done in the time frame you commit to.
• You successfully swim in the waters of Agile project management techniques (scrum boards, standups, demos, reviews).
• Must love mentoring and sharing knowledge.
• Must love dad jokes.

Your formal qualifications are the following:

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