Top Machine Learning Jobs
As the Lead Machine Learning Engineer, you will develop and implement machine learning models for digital advertising performance, collaborate with software engineers, innovate ML solutions, mentor a growing team, and ensure models are effective and scalable.
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Manager of Generative AI team responsible for managing and leading researchers and engineers. Leverage expertise in LLMs and generative models to create AI roadmap. Work on cutting-edge technologies and collaborate with professionals.
The Machine Learning Engineer will optimize AI inference systems, develop runtime inference services, and collaborate with teams to enhance AI capabilities. Responsibilities include designing production systems, conducting code reviews, and implementing robust data processing systems.
The MLOps Engineer will develop systems and APIs for inference and fine-tuning of large language models, implement runtime systems for production-level ML training, and collaborate with various teams for deploying and maintaining ML inference systems.
As an ML Engineer at Together AI, you will develop a platform for customizing open-source models, collaborate with product and research teams, ensure API reliability, and contribute to the open-source AI ecosystem. Key responsibilities include building systems, creating tooling, ensuring stability, analyzing methods, and developing new features. Ideal candidates have 2+ years of ML deployment experience, knowledge of fine-tuning methods, strong Python or Go skills, and a passion for reliable tools. Standout experiences include large-scale system development, advanced fine-tuning methods, open-source contribution, and ML workload management on Kubernetes.
Research and build the next generation AI platform at Together AI, design large-scale distributed training systems and low-latency/high-throughput inference engine, stay up-to-date with latest advancements in machine learning systems.
AI Researcher responsible for developing novel architectures, system optimizations, and algorithms to push the frontier of open models. Collaborate with cross-functional teams and stay updated on the latest advancements in machine learning. Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or related field required.
As a Machine Learning Scientist, you will drive research in generative modeling technologies for biomolecular design, develop deep learning methods for protein prediction, curate datasets, and collaborate with biology teams. The role requires implementing and analyzing computational approaches and shaping the scientific vision of the company.
Featured Jobs
As a Senior Machine Learning Engineer at Radiant Security, you will design and develop scalable ML solutions for SaaS applications. You will collaborate with data scientists, manage ML lifecycle, ensure efficient model serving, and maintain data integrity, while keeping up with the latest technologies to enhance outcomes.
The role involves developing generative models and algorithms for protein design, scaling systems for data utilization, collaborating with lab teams, and engineering ML systems for therapeutic applications.
The Senior AI & ML Consultant will architect and implement AI and ML solutions using OpenAI and Azure ML, lead project lifecycles, develop strategic roadmaps, and facilitate workshops to enhance AI understanding among clients. The individual will address complex business needs with innovative AI solutions while ensuring fairness in AI deployment.
In this role, you will design and build advanced search and recommendation algorithms that improve the customer experience at Wayfair. You will develop scalable machine learning models while collaborating with cross-functional teams and addressing complex challenges. You will also stay abreast of the latest advancements in ML.
Design and implement infrastructure for training, evaluating, and deploying deep learning models for self-driving semi trucks. Develop and optimize training pipelines, track metrics, and enable continuous integration and deployment of model improvements in collaboration with cross-functional teams.
Design and develop algorithms to model interactions in enterprise cybersecurity, apply AI and graph analysis techniques, build solutions balancing complexity and performance, and collaborate with engineering teams on ML infrastructure and data pipelines.
Conduct world-class research on data analytics and contribute to the long-term research agenda in large-scale data analytics and machine learning. Develop AI/Machine learning models to detect credit card information attacks. Collaborate with product stakeholders to formulate and solve complex technical data problems.
The Senior Machine Learning Engineer will work on developing AI-powered software, fine-tuning large language models, conducting multimodal product research, and ensuring model alignment to improve user experience at Scribe.
The Machine Learning Engineer will work on AI-powered software development, focusing on multimodal capabilities including vision and audio. Responsibilities include designing data pipelines for model training, improving model performance through experimentation, and collaborating with various teams.
The Machine Learning Engineer at Scribe will design and implement advanced AI techniques, optimize model performance, and create benchmarking infrastructure. Responsibilities include translating AI innovations into features, working on memory management, and collaborating with engineering teams to enhance model quality.
As a Senior Machine Learning Engineer at Enigma, you will develop scalable ML systems, enhance entity resolution algorithms, and improve machine learning infrastructure, directly impacting business decisions for customers. You will collaborate with data scientists and engineers to innovate and maintain high-performance systems.
The Machine Learning Research Scientist will develop and research state-of-the-art NLP models to enhance market research. The role involves predictive modeling, algorithm development for large-scale applications, and effective communication of technical concepts to non-technical stakeholders.
Design, train, and deploy deep learning models utilizing extensive labeled and unlabeled data from a fleet of vehicles, focusing on generative and foundation models to advance autonomous driving capabilities.
The Senior Data Scientist will support product security efforts by developing machine learning solutions, building data pipelines, and integrating models into game development while collaborating with various departments. The role involves communicating analysis results to both technical and non-technical teams.
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As a Staff Data Scientist at Coinbase, you will build advanced models, provide technical mentorship, and develop novel experimentation techniques to drive business value. Your role will involve creating sequential features based on user behavior and quantifying the impact of negative experiences on the platform.
Lead the design, development, and improvement of machine learning models for 3D computer vision in an innovative photogrammetry platform. Responsibilities include optimizing ML systems, deploying models, and staying updated on advancements in the field. This role requires hands-on leadership and a solid background in machine learning and computer vision.
As a Senior Machine Learning Engineer, you will design and develop machine learning applications, conduct experiments, work collaboratively with engineers, engage with clients, and mentor project teams, focusing on practical AI solutions for clients.
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