ML Engineer
3 days ago
We are seeking a talented Machine Learning Engineer with strong software engineering skills to contribute to impactful R&D projects. This role centers on engineering solutions, collaborating with the OpenX Data Science team to optimize and advance the ML platform by providing robust infrastructure and support.
Job Description:This is a key position in our team where you will be responsible for designing, developing, and delivering innovative features and functionalities. You will assist in migrating model training pipelines across different technologies or transitioning model implementations to other frameworks, providing strategic guidance for optimizing models and enhancing model training pipelines.
Key Responsibilities:- Analyze and enhance the efficiency, scalability, and stability of machine learning model training pipelines.
- Develop, maintain, and monitor the infrastructure responsible for training ML models by automating pipeline-related tasks, adding performance metrics, helping troubleshoot issues, and creating alerts.
- Optimize models by profiling, analyzing flame graphs to identify performance bottlenecks, and applying faster computational graph operations or full model transformations such as pruning, quantization, or hardware acceleration.
- Collaborate with team members to deploy, manage, and integrate machine learning models.
The successful candidate will have experience with cloud platforms and their machine learning capabilities, particularly Google Cloud Platform's Vertex AI. They will also have excellent communication skills in both Polish and English.
Requirements:- 7+ years of experience in a similar role and a Bachelor's degree in Computer Science or a related field.
- Extensive expertise in Python programming and software engineering best practices.
- Demonstrated proficiency with machine learning frameworks such as TensorFlow, Keras, or PyTorch.
- Familiarity with basic SQL for querying and data manipulation.
- Hands-on knowledge of ML pipelines, particularly Kubeflow Pipelines.
- Basic understanding of machine learning techniques sufficient to comprehend and utilize models developed by data scientists.
- Experience with cloud platforms and their machine learning capabilities, particularly Google Cloud Platform's Vertex AI.
- Private healthcare.
- Training budget.
- Flat structure.
- Small teams.
- Lunch card.
- Free coffee.
- Free parking.
- In-house trainings.
- Modern office.
- No dress code.
- Bike parking.
- Shower.
- Free snacks.
- Free beverages.
- Playroom.
$120,000 per year.
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