Machine Learning Engineer

deepsense.ai is seeking a skilled Machine Learning Engineer to join our team, focusing on developing and deploying AI-driven solutions. In this role, you’ll work alongside our data engineers and scientists to build scalable systems that address complex challenges across various industries. Your contributions will span the full lifecycle of AI development, from initial design to final deployment, emphasizing innovative and impactful solutions.

Responsibilities:

• build and deploy scalable machine learning models to solve real-world challenges,
• translate business requirements into machine learning tasks and goals,
• optimize data pipelines for model training and deployment,
• implement automated processes for model updates and deployment,
• ensure AI models integrate smoothly into client environments,
• keep up with new technologies and methodologies and apply them in action,
• share knowledge through deeptalks and workshops.

You must have:

• at least 4 years in Machine Learning, including experience in deploying models,
• strong Python skills and familiarity with other object-oriented languages,
• experience with machine learning frameworks (PyTorch) and big data technologies,
• familiarity with Docker, Kubernetes, and cloud platforms for ML deployment,
• very effective communication skills, both written and verbal,
• ability to solve problems and communicate complex ideas effectively.

Bonus Skills:

• experience with Generative AI and Large Language Models (LLMs),
• experience with Computer Vision projects,
• familiarity with NoSQL and Vector databases,
• exposure to backend engineering – asyncio, microservices, production databases.

We offer:

• competitive salary and benefits package,
• opportunity to work on cutting-edge AI projects with a diverse range of clients and industries, driving solutions from development to production,
• collaborative and supportive work environment, where you can grow and learn from a team of talented professionals,
• an opportunity to participate in conferences and workshops,
• an opportunity to participate in Tech Talks (internal training and seminar sessions),
• flexible working hours and remote work options.