Machine Learning Engineer

Cellanome is a well-funded start-up focused on tackling significant challenges in biology through advanced technology. The Machine Learning Engineer will collaborate with various teams to develop algorithms for data analysis and workflow automation, ensuring integration into the broader software ecosystem.

Responsibilities:

• Design, develop, and optimize advanced algorithms for workflow automation, which include computer vision and computational geometry components
• Develop signal-processing and image-analysis algorithms using classical methods as well as modern AI/ML approaches, including neural networks
• Perform system-level analysis, simulation, and validation to ensure algorithm performance meets product requirements
• Collaborate with cross-functional hardware, software, and product engineering teams to integrate algorithms into our broader software ecosystem
• Optimize algorithms for deployment on edge devices, GPUs, and high-performance computing environments with considerations for latency, throughput, and memory efficiency
• Create technical documentation, validation reports, and performance metrics to support product development and cross-team collaboration

Requirements:

• Typically requires a Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field with 5+ years of relevant experience, or a Master's degree with 3+ years of relevant experience
• Experience developing, implementing, and validating algorithms for optimization, automation, sensing, data analysis, or image-processing applications
• Strong programming skills in Python with experience developing production-quality, maintainable, and well-documented code
• Solid understanding of software development fundamentals, including debugging, version control, testing, and code optimization
• Familiarity with AI/ML concepts and workflows, including data preprocessing, model training, evaluation, and deployment
• Experience with image analysis, computer vision, signal processing, or data-driven algorithm development
• Understanding of mathematical foundations relevant to algorithm development, including linear algebra, probability/statistics, optimization methods, and estimation theory
• Experience applying algorithmic techniques such as optimization, dynamic programming, numerical methods, or statistical modeling to solve engineering problems
• Familiarity with workflow automation, process optimization, or development of efficient data-processing pipelines
• Ability to analyze complex technical problems, evaluate tradeoffs, and develop scalable algorithmic solutions
• Excellent communication skills and ability to work independently and collaboratively in a multidisciplinary team environment
• Proficiency in C++, C#, or other high-performance programming languages for algorithm deployment and system integration
• Experience developing AI/ML algorithms for image analysis, pattern recognition, anomaly detection, or automated decision systems
• Advanced familiarity with modern computer vision and deep learning architectures, including Vision Transformers (ViTs), CNNs, object detection, segmentation, or multimodal AI models
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or similar platforms
• Experience optimizing algorithms for performance, scalability, memory efficiency, or real-time execution
• Familiarity with optimization and estimation techniques such as convex optimization, Kalman filtering, Bayesian estimation, nonlinear optimization, or stochastic methods