Team Leader ML Engineer

Position Summary: As a Team Leader at DeepKeep.ai, you will play a pivotal role in leading and bridging our talented research team with our proficient engineering squad. Your primary responsibility will be to lead the transformation of complex research ideas into scalable, robust machine learning applications deployable in production environments. This hands-on role demands a deep understanding of machine learning technologies and the ability to innovate and implement solutions within a commercial context.

Key Responsibilities:

• Lead the translation of advanced research prototypes into scalable, production-grade software.
• Optimize the utilization of machine learning models, implementing techniques such as early stopping and optimization against adversarial attacks.
• Collaborate closely with data scientists to understand research findings and translate them into practical, scalable solutions.
• Design and implement efficient machine learning systems compatible with diverse data types and integrable with technologies like transformers.
• Drive ambitious projects through collaboration with cross-functional teams, ensuring seamless integration of machine learning technologies across our product suite.

Who we're looking for:

• A visionary leader with substantial experience in software engineering and machine learning development.
• Ability to translate intricate, algorithmic prototypes into scalable, market-ready solutions.
• Proficiency in machine learning frameworks (e.g., PyTorch, TensorFlow) and adapting them for modern computing environments (GPU, distributed computing).
• Expertise in specialized machine learning databases and optimizing the performance of ML applications.
• Hands-on experience in MLOps, capable of architecting and overseeing large-scale ML systems.
• Strong grasp of statistical concepts and algorithms essential in machine learning.
• A collaborative team player known for effective teamwork, knowledge sharing, and thriving in dynamic environments.

Qualifications:

• Minimum 6 years of development experience, with at least two years as a machine learning engineer.
• Exceptional Python coding skills, including experience with APIs, Kafka, SQL, NoSQL, and other relevant technologies. Knowledge of strictly typed languages is advantageous.
• Demonstrated leadership in managing end-to-end ML projects (pipelines, models, datasets, backend).
• Proficiency in machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and data processing libraries (e.g., NumPy, Pandas).
• Strong problem-solving and critical thinking skills.
• Familiarity with ML databases and vector databases is advantageous.
• Solid foundation in MLOps, with hands-on experience in designing and managing large-scale ML infrastructures.
• Understanding of statistical concepts and algorithms used in machine learning.