Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer

Location: Zurich / Remote

Contract: 6-month Freelance (with possibility of extension)

Company Overview:

DeepRec.ai is collaborating with a rapidly growing, innovative Biotech company focused on transforming Drug Discovery through AI. if you're passionate about AI for Science, we're seeking a Senior Machine Learning Engineer to join their growing team.

Job Description:

As a Senior Machine Learning Engineer, you will be joining a high-impact, mission-driven team working on the forefront of AI research. You'll have the opportunity to contribute to the development of generative modeling techniques and large language models. Your role will involve building and optimizing state-of-the-art deep learning models, deploying them at scale, and working in a collaborative environment with some of the best minds in AI and Biotech.

This is a unique opportunity to make a significant impact at a well-funded, fast-growing company that is defining the future of AI in the Biotech space.

Key Responsibilities:

• Design, implement, and deploy machine learning models with a focus on large language models and generative modeling.
• Fine-tune and optimize deep learning models at scale, applying advanced hyperparameter tuning techniques.
• Collaborate closely with a highly skilled, interdisciplinary team of researchers, engineers, and Biotech experts to integrate AI solutions into real-world applications.
• Drive continuous improvements in model performance and scalability.
• Stay up-to-date with the latest research and technological advancements in AI/ML and contribute innovative ideas to the team.

Required Skills:

• 3+ years of industry experience in Machine Learning and AI.
• Strong expertise in large language models (LLMs), including experience coding, deploying, evaluating, and fine-tuning these models.
• Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or similar, and a strong understanding of model training and evaluation.
• Proficiency in deploying machine learning models at scale in cloud-based environments (AWS, GCP, Azure, etc.).
• Experience with hyperparameter tuning and optimization techniques.
• Solid understanding of machine learning algorithms and techniques, particularly in generative modeling and NLP.