<div>Simulmedia is seeking an experienced <b>ML Engineer</b> to join our growing <b>Data Science</b> team and help bridge the gap between research and production. In this role, you will play a key part in turning experimental work into reliable, long-term solutions that deliver value at scale. As an <b>ML Engineer</b>, you will work closely with data scientists and data engineers to transform prototypes, analyses, and models into scalable, maintainable, and efficient production systems.</div><div><br /></div><div><b>This position is based in either Kyiv or Lviv, Ukraine, with team members across major cities including Kyiv, Lviv, and Kharkiv. The team primarily works remotely, with occasional in-person meetings in the Kyiv office.</b></div><div><br /></div><div><b>Responsibilities</b></div><div>●<span>      </span>Collaborate closely with data scientists to turn research and prototypes into reliable, production-ready solutions.</div><div>●<span>      </span>Develop and maintain scalable pipelines that power data, feature, and model workflows across the organization.</div><div>●<span>      </span>Ensure solutions are efficient, reproducible, and maintainable, supporting long-term use and growth.</div><div>●<span>      </span>Monitor and troubleshoot deployed systems, optimizing performance and reliability over time.</div><div>●<span>      </span>Apply software engineering best practices, including testing, automation, version control, and deployment processes.</div><div>●<span>      </span>Contribute to a growing team, helping to improve workflows and support the adoption of data-driven solutions.</div><div><br /></div><div><b>Qualifications</b></div><div>●<span>      </span>Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.</div><div>●<span>      </span>7+ years of professional experience in Data Science Engineering, or in software engineering roles with significant exposure to data science workflows.</div><div>●<span>      </span>Proficiency in Python, with experience developing clean, maintainable, and production-ready code.</div><div>●<span>      </span>Proficiency in SQL and relational databases, for working with large-scale datasets.</div><div>●<span>      </span>Solid understanding of software engineering best practices, including version control, testing, and containerization.</div><div>●<span>      </span>Ability to troubleshoot complex problems, take ownership of solutions, and quickly learn new tools or technologies.</div><div>●<span>      </span>Strong collaboration and communication skills, able to work effectively with a growing Data Science team.</div><div>●<span>      </span>Comfortable communicating and coordinating with <a href="http://U.S.-based">U.S.-based</a> colleagues.</div><div>●<span>      </span>Ability to work 11 am - 8 pm EEST.</div><div><br /></div><div><b>Bonus points for</b></div><div>●<span>      </span>Familiarity with AWS cloud services such as S3, Kubernetes, Lambda, and Redshift for data and ML workflows.</div><div>●<span>      </span>Data ETL pipelines</div><div>●<span>      </span>Understanding MLOps practices (model deployment, monitoring, CI/CD).</div><div>●<span>      </span>Knowledge of machine learning workflows and ability to work with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).</div>

Simulmedia

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