Hybrid Deep Learning Machine Learning Engineer Deep Learning Machine Learning Engineer with verification

Location: Remote EMEA/APAC

Contract duration: Minimum one year duration, extension possible as the client's department is growing

Are you excited about leveraging your deep learning expertise to unlock the potential of single-cell and genomic data? Join our client's Single Cell team as a Deep Learning Machine Learning Engineer!

You will play a pivotal role in designing and implementing state-of-the-art machine learning algorithms and pipelines. This is a unique opportunity to be at the forefront of bioinformatics and computational biology, contributing to its advancement through your machine learning prowess.

Key Responsibilities:

• Design, develop, and implement deep learning models, pipelines, and libraries for single-cell and genomic data analysis.
• Collaborate with scientists and engineers to understand complex biological problems and create machine learning solutions.
• Pre-process and engineer high-dimensional datasets for machine learning analysis.
• Evaluate and optimize the performance of machine learning models.
• Develop and implement automated pipelines for data processing and model training.
• Create various visualizations and reports for trained models.
• Stay abreast of the latest advancements in deep learning and related fields.
• Document your work clearly and communicate technical concepts to both technical and non-technical audiences.

Qualifications:

Required:

• Ph.D. in a quantitative discipline (or M.S. with 3+ years, or B.S. with 5+ years of experience in AI/ML solutions).
• Experience with ML, NLP, and GenAI technologies using structured and unstructured data.
• Proficiency in Python and Rust, and deep learning frameworks like PyTorch, Jax, ONNX.
• Experience with ML libraries (e.g., transformers, sklearn) and visualization tools (e.g., Matplotlib, Seaborn).
• Proven success in developing traditional and transformer-based NLP models, optimizing LLMs, and GenAI systems.
• Strong experience with CI/CD pipelines (e.g., Docker, Kubernetes, GitHub) and ML platforms (e.g., AWS SageMaker, Databricks).

Preferred:

• Experience in the pharma industry and fast-paced research environments.
• Familiarity with single-cell/genomic data and tools (e.g., Scanpy, AnnData).
• Strong communication, collaboration, and presentation skills.

Are you ready to apply your deep learning skills to make a significant impact in the field of bioinformatics? We want to hear from you!