Would you like to be part of an exciting and impactful product?

Make our world a better and safer place while using cutting-edge technologies at scale?

DeepKeep is an innovative, industry leading solution for defending AI.

As a Senior ML Engineer, you will have the opportunity to participate in a breakthrough AI security platform that leverages cutting-edge technologies while working in an agile development lifecycle.

What you'll do:

• Serve as the crucial link and central figure between research and engineering teams.
• Engage in deep collaboration with researchers to transform research insights into broader applications.
• Tackle intricate challenges with scalable, straightforward solutions from initial proof of concept to production deployment.
• Drive the development of groundbreaking technology solutions, expanding the limits of our technical capabilities.
• Excel as a machine learning authority: Master the technologies behind the training, fine-tuning, and deployment of the most advanced models. You’ll work on the inner workings of models, focusing on crafting robust security solutions for them.

Who we're looking for:

• A remarkable individual who balances a strong footing in both software engineering and ML development realms.
• Expertise in transforming algorithmic prototypes into market-ready products, directly influencing the company's growth.
• A passionate enthusiast in reverse engineering: Proficient in dissecting complex systems to derive meaningful insights.
• A proficient coder: Versatile in various programming languages, devising elegant, problem-solving software solutions - who’s extremely proficient in Python.
• A dynamic team collaborator: Known for effective teamwork, open knowledge sharing, and excelling in a dynamic environment.
• Capable of conveying intricate systems and features with both depth and clarity.
• Daily engagement with cutting-edge fields: machine learning, big data, and cloud computing.
• Minimum 5 years of practical experience in developing machine learning and statistical modeling solutions.

Qualifications:

• Master’s degree in Computer Science/Software Engineering or substantial practical experience with a bachelor's degree in a STEM subject.
• An advocate for innovation and advanced technology, continually exploring the realm of possibilities.
• Proficient in Python programming, design patterns and knows strict typing languages.
• Experienced in data science tools (e.g. PyTorch, TensorFlow, Pandas, scikit-learn, etc).
• Skilled in adapting machine learning techniques to optimize for modern parallel computing environments (including distributed clusters, multicore SMP, and GPU).
• In-depth knowledge and hands-on experience with at least one type of ML model (vision, NLP, voice, etc) encompassing training, fine-tuning, and their applications.
• Solid experience in MLOps, adept at designing and managing expansive ML infrastructures.
• Possess strong problem solving and critical thinking skills.
• Strong foundation in MLOps, with hands-on experience in designing and managing large-scale ML infrastructures.
• Solid understanding of statistical concepts and algorithms used in machine learning.