ML Ops Engineer

Role Machine Learning Ops Engineer

Location – Amsterdam Netherlands

Duration: 612 month contract

Working Mode: Hybrid

Job Description:

o You have 5 years of work experience with Python and AI/ML standard libraries such as pandas scikitlearn xgboost

Nicetohaves:

Data processing libraries and frameworks (pydantic pandera)

Web frameworks (such as FastAPI Flask ...)

CLI frameworks (Typer Click ...)

General MLOps tools and frameworks (MLFlow Azure ML Studio ...)

Version control tools for ML datasets and models (DVC Azure ML Dataset ...)

Monitoring libraries and solutions (such as NannyML Evidently AI ...)

Distributed processing libraries and frameworks (such as Ray Dask PySpark ...)

Pipelinebuilding and orchestration libraries (such as Metaflow ZenML Kedro Airflow Dagster ...)

General Python development tool (pytest coverage tox mypy black ruff uv pipcompile ...)

o You can write both objectoriented and functional code and understand concepts such as (de)coupling coherence inheritance composition.

o You make sure the code that you and your colleagues write is thoroughly tested (unit integration endtoend stress/performance).

o You love and regularly use data validation and type hints.

o You know how to turn a messy jupyter notebook into a productiongrade piece of code.

Although we'll apply all possible preventive measure to prevent this from ever happening.

o You know how to package a python application or library for distribution

o 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 a good understanding of Machine Learning algorithms and their applications in NLP.

You have work experience with at least one Cloud Provider preferably Azure Cloud.

You have experience with Unix/Linux command line tools and scripting (shell bash):

o 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:

o You could handle using SQL to extract transform and load data (ETL/ELT).

o 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.

o You are able to identify the MLOps maturity gaps and provide inputs for modernization efforts.

Nontechnical

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 always on the lookout for modernization opportunities.

You stay uptodate with new tools technologies and approaches within the domain.

You are a wellintegrated team player.

You are able to estimate your shortterm 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).

You stand to promote MLOps and advocate for its usage and necessity across the organization.

Must love mentoring and sharing knowledge.

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