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Machine Learning Engineer
3 months ago
Success Criteria
- Collaborate with cross-functional teams to identify opportunities for applying machine learning techniques to solve complex problems
- Design, develop, and deploy machine learning models and algorithms to address specific business needs and challenges
- Implement scalable and efficient software solutions to integrate machine learning models into production systems
- Optimize and fine-tune machine learning algorithms for improved performance and accuracy
- Conduct thorough testing and validation of machine learning models to ensure robustness and reliability
- Stay updated on the latest developments and advancements in machine learning and communicate promising research directions to the team
- Provide technical guidance and mentorship to junior team members
- Master's degree or Ph.D. in Computer Science, Engineering, Mathematics, or a related field
- 3+ years of demonstrated experience in a wide variety of ML methods with a focus on a specialization such as dexterous manipulation with reinforcement learning or imitation learning, computer vision for robotics, or natural language processing
- 4+ years of experience in software engineering, with a focus on developing and deploying production-grade applications
- Working experience with ROS2
- Development experience with parallel computing such as CUDA, OpenMP, SSE, etc.
- Experience with Atlassian tools; Jira, GitLab, Confluence
- Experience taking ML models to production
- Hands-on experience with popular machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
- Experience with cloud platforms (e.g. AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is a plus
- Familiarity with robotics principles and technologies is highly desirable
- Publications in leading AI, ML or robotics conferences
- Strong proficiency in programming languages such as Python or C++
- Extensive knowledge of machine learning techniques and algorithms, including but not limited to supervised and unsupervised learning, deep learning, reinforcement learning, and natural language processing
- Working knowledge of PyTorch and/or TensorFlow
- Excellent problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment
- Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders
- Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems
- Optimistic listening and conflict resolution capabilities
- Demonstrated ability to influence others without authority
- Eager to take on new challenges with tenacity and positivity
- Patience, persistence, and attention to detail when resolving performance issues
- Obsession with bringing human-like intelligence to machines
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