Job Title: Machine Learning Engineer, Large Language Models (LLM)
Location: On-Site (Flexible)
Company: Genentech
Industry: AI, Natural Language Processing, Machine Learning
About the Role:
Are you ready to dive deep into the world of large language models (LLM) and push the envelope on AI capabilities? We are seeking a talented Machine Learning Engineer to join our team and focus on advancing the next generation of LLM technologies. As a key member of our AI engineering team, you’ll work on cutting-edge NLP models, tackling complex problems and building systems that can understand and generate human-like text at an unprecedented scale.
This role is an exciting opportunity to develop sophisticated, high-performance models that will shape the future of communication, automation, and artificial intelligence. You’ll have the chance to work with top-tier researchers and engineers to enhance the capabilities of LLMs, from training massive models to optimizing them for real-world applications.
What You’ll Do:
Build and Optimize LLMs: Work on designing, implementing, and fine-tuning large-scale transformer models for natural language understanding, generation, and reasoning.
Model Training & Scaling: Manage and execute large-scale model training, including optimizing performance, reducing latency, and handling large datasets efficiently.
Innovate with Cutting-edge Techniques: Implement state-of-the-art techniques to improve model accuracy, efficiency, and generalization, and stay on top of the latest research in LLM architectures and NLP.
Deployment & Integration: Help deploy and integrate models into real-world applications, ensuring they function effectively across a variety of platforms and environments.
Collaborate Across Teams: Work closely with data scientists, researchers, and product teams to integrate LLMs into scalable, production-ready systems.
Experiment and Iterate: Run experiments to evaluate new ideas, improve model performance, and iterate on cutting-edge architectures and algorithms.
Mentorship and Growth: Provide mentorship to junior engineers, helping them navigate the complexities of LLMs and fostering a collaborative, innovative team culture.
What We’re Looking For:
3+ years of experience in machine learning or deep learning, specifically with natural language processing or large-scale transformer models (e.g., GPT, BERT).
Expertise in machine learning frameworks such as TensorFlow, PyTorch, or JAX and deep familiarity with transformer architectures and large-scale training techniques.
Strong programming skills in Python, with experience in optimizing and parallelizing code for performance and scalability.
Solid understanding of NLP fundamentals, including tokenization, embeddings, attention mechanisms, and transfer learning.
Experience with large-scale distributed systems, cloud computing (e.g., AWS, GCP, Azure), and tools for managing big data workflows.
Proven ability to deploy machine learning models to production environments, including ensuring robustness, reliability, and performance under heavy usage.
Strong problem-solving skills with the ability to manage complex, long-term research and engineering projects.
Excellent communication skills and the ability to collaborate effectively in a multidisciplinary team.
Bonus Points:
Experience working with cutting-edge LLMs such as GPT-3, T5, or BART.
Familiarity with specialized areas of NLP such as sentiment analysis, question answering, summarization, or language translation.
Contributions to the open-source community or involvement in AI research publications.
Experience working with AI/ML deployment pipelines (e.g., Docker, Kubernetes, CI/CD for ML models).
Advanced degree (M.S./Ph.D.) in Computer Science, Machine Learning, AI, or a related field.
Why Genentech?
Innovative Environment: Work on high-impact projects that shape the future of AI technology and have real-world applications across industries.
Collaborative Culture: Join a team of passionate engineers, researchers, and AI experts, where knowledge-sharing and innovation are at the forefront of everything we do.
Growth Opportunities: With ample opportunities for mentorship, learning, and advancement, you’ll continue to grow as a leader in the field of machine learning.
Flexible Work Options: Choose the working style that suits you—remote, hybrid, or on-site—while maintaining a healthy work-life balance.
Competitive Compensation: Enjoy a competitive salary, equity options, and performance-based bonuses, along with comprehensive benefits.
Cutting-Edge Technology: Access state-of-the-art computing infrastructure and resources to enable your work at the forefront of AI.
