Role Description The Machine Learning Engineer will work in close collaboration with the core instrument, assay and software teams to develop algorithms for data analysis and workflow automation. This role reports to the Sr. Director AI and can be based in our San Diego CA or Foster City CA offices, or remotely (if candidate not located within commutable distance of either office). - 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. Qualifications - 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. Requirements - 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. Benefits - Competitive total compensation packages, including base pay, benefits, and equity. - Estimated base salary range for this position in California is $160,000 - $215,000/year. - Comprehensive employment package that includes a competitive salary, generous stock options, great individual and family health plans, a 401(k), and flexibility to balance work and life.

• Build scalable pre-training pipelines for foundation models, optimizing throughput and efficiency. • Implement distributed training strategies across GPUs/TPUs and high-performance clusters. • Collaborate with researchers to translate experimental setups into production-ready workflows. • Develop monitoring and fault-tolerance systems to ensure reliable large-scale training. • Continuously benchmark and tune performance across hardware and software stacks.

• Lead the technical enablement of machine learning teams in advanced use of the platform. • Drive and coordinate migrations of legacy models to the new platform with technical rigor and without regressions. • Systematically identify bugs, documentation gaps and structural adoption barriers — proposing and tracking resolutions directly with product teams. • Produce technical reference materials: usage architectures, production-grade code examples, runbooks and advanced guides. • Translate qualified community feedback into prioritized inputs for the platform roadmap. • Lead technical sessions, workshops and architecture reviews with engineering and data science teams. • Act as the technical authority and point of contact between the platform and its consumer teams.

Role Description We are searching for a talented Senior/Staff Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we're dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability. What you'll be doing: - Lead the creation and optimization of advanced machine learning algorithms—from developing new methods to refining existing techniques—to enhance advertising effectiveness and ROI using deep ML expertise. - Own the end-to-end development of production-grade ML models: write efficient, scalable code and collaborate with Data Engineers to deploy and integrate algorithms into live systems. - Drive the prototyping and rigorous testing of innovative algorithms and data pipelines using historical data to validate performance and scalability; lead iterative improvements based on data-driven insights. Qualifications - 3+ years of industry experience - Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus. - Have the ability to take an ambiguously defined task, and break it down into actionable steps - Have a comprehensive understanding of statistics, optimization and machine learning - Are proficient in coding, data structures, and algorithms - Enjoy working in a friendly, collaborative environment with others Benefits - Highly competitive salary - Retirement/401K/Pension Savings globally - Competitive Paid time off packages including birthdays off! - Access to a comprehensive mental health care program - Health benefits from day one of employment - Work from home reimbursements - Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto - Robust training and onboarding program - Coverage and support of personal development initiatives (conferences, courses, books etc) - Access to StackAdapt programmatic courses and certifications to support continuous learning - An awesome parental leave program - A friendly, welcoming, and supportive culture - Our social and team events!