Machine Learning Engineer – LLM & Generative AI

Key Skills

ChatGPT, DataOps, Deep Learning, Generative AI, Large Language Models - LLMs, Leadership Skill, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, TensorFlow

Job Description

We are looking for a highly motivated and talented Machine Learning Engineer to join our AI team. The ideal candidate will have experience in Large Language Modeling (LLM) and DataOps. We are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, then this is the perfect job for you!

Opportunity: Machine learning experts on our team can utilize applied science and software development skills to help tweak Foundation Models that help us address some of the hardest problems towards our vision in making insights from complex Industrial data simple & easy to access. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning, AI, and Industrial data architects making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.

This position offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of saving lives with Industrial Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the Industrial domain. Join us and make a significant impact on the future of Industrial DataOps.

What You'll Do

• Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
• Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
• Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
• Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
• Deliver the next generation of innovation in trustworthy Industrial Data Insights & Collaboration

Who You Are

• Extensive software engineering experience in building high performance, large-scale ML systems (Preferably 3 to 5 years of industry experience in the relevant fields).
• Strong communication skills and the ability to work effectively in a collaborative research environment.
• Demonstrated leadership abilities, with experience in guiding and mentoring a team of ML engineers.
• Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems.
• Strong theoretical and practical background in NLP including experience with state-of-the-art LLM architectures optimized for handling large context and low inference cost.
• Advanced degree, ideally a Ph.D., in Computer Science, Electrical Engineering, or a related field with specialized research in areas such as machine learning, NLP, Large Language Models (LLMs), multi-modal foundation models, and generative AI techniques.
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI.
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code.
• 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
• Experience with distributed parallel training, large-scale multi-modal foundation and generative models strongly preferred.
• Collaborate on modeling techniques to support the full spectrum of LLM tuning including prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF), parameter-efficient tuning, and fine-tuning strongly preferred.
• Familiarity with training multi-modal foundation models and relevant frameworks strongly preferred.
• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments.
• Experience with RAG, dual encoders, or related fields strongly preferred.
• Experience with JAX.
• A track record of publications and contributions to the machine learning and natural language processing communities strongly preferred.