Senior Machine Learning Engineer
New
T
TalenticaArtificial Intelligence
The successful candidate will work from Poland, No fixed time zone, team members are expected to maintain sufficient working-hours overlap with their immediate colleagues.Full-TimeSenior
SalaryThe company does not publish a fixed external salary range. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates.
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Job Details
- Required Skills
- PythonMachine LearningPyTorch
Requirements
- Proven experience building and shipping Machine Learning systems used by real users.
- Strong understanding of how modern Machine Learning models behave and fail in production environments.
- Ability to write high-quality production code and think in complete systems rather than isolated scripts.
- Strong ownership and the ability to work independently from an ambiguous problem through production delivery.
- Experience working across data, model training, evaluation and inference.
- Ability to communicate clearly, learn quickly and improve systems through continuous iteration.
- Sound technical judgment when balancing model quality, latency, cost, reliability and safety.
- Ability to mentor peers and raise the technical standard of a Machine Learning team.
- Proficiency in Python.
- Experience with PyTorch or JAX.
- Experience with GPU-based training and inference systems.
Responsibilities
- Build core Machine Learning systems powering a proactive, long-horizon AI product.
- Own work end-to-end across data preparation, training, evaluation, inference and continuous iteration.
- Transform research concepts into reliable systems operating in production.
- Diagnose model failures and system-level issues using real production signals.
- Work iteratively: ship solutions, measure outcomes, refine them and repeat.
- Collaborate closely with research, product and engineering teams to deliver measurable user impact.
- Mentor other Machine Learning engineers and review their work through technical judgment and practical example.
- Operate under real production constraints, including latency, cost, reliability and safety.
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