Top Machine Learning Engineer Jobs

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

The Senior Software Engineer will innovate in AI, lead software development lifecycle, design microservices, mentor peers, and ensure engineering excellence.

Lead the design and development of machine learning solutions, overseeing the entire software development lifecycle and mentoring engineers. Drive innovation in Generative AI and high-performance systems.

Build and scale the infrastructure layer for visual intelligence: optimize VLM inference and GPU serving, design multimodal APIs and structured outputs, ensure scalable backend systems, reliability, observability, CI/CD, and developer experience. Drive 0→1 product work with strong testing discipline, schema validation, and performance optimization.

Build and deploy LLM-based chatbots and machine learning models, integrate agents with enterprise databases and APIs, perform data preprocessing and model evaluation, automate data pipelines, and collaborate with internal teams and clients.

Build and own LLM systems and infrastructure for Overtone's product: prompt architecture, evaluation pipelines, model experimentation, serving, fine-tuning (SFT/DPO/RLHF), vector DBs and personalization, observability tooling, and lightweight matching models. Collaborate cross-functionally to deploy reliable, auditable AI features in production.

Build and ship ML-powered SaaS features end-to-end: design data/feature pipelines, develop and deploy models (forecasting, ranking, recommendations, optimization), define evaluation/A-B testing, monitor drift, integrate models into product workflows, influence roadmap, mentor teammates, and support MLOps and cloud data infrastructure to ensure measurable product impact.

Design, develop, and deploy scalable AI/ML solutions on cloud platforms. Architect high-performance systems for predictive analytics, NLP, and computer vision; implement AI pipelines, integrate models with enterprise systems, apply big-data processing and advanced ML techniques, and ensure Responsible AI practices. Collaborate with cross-functional teams to translate prototypes into production and evaluate model performance.

Develop, train, evaluate, and deploy spatial generative AI models for home renovation and design. Define inference framing, prepare image-based datasets with labeling partners, iterate with user feedback, and deploy performant models into production architecture.

Design, fine-tune, and deploy LLMs and RAG pipelines in private, secure environments. Build multi-agent systems, private inference infrastructure, evaluation frameworks, and observability tooling. Collaborate with platform teams to ensure secure, scalable production AI for enterprise customers.

The role involves designing, building, and deploying computer vision models for vehicle damage detection, covering the entire ML lifecycle and collaborating across teams.

Lead the technical direction of DeepWalk's computer vision platform, enhancing ML systems and data pipelines for sidewalk inspection.

The role involves designing and operating AI systems, building data pipelines, fine-tuning models, and mentoring team members while collaborating with product and data science teams.

The Machine Learning Engineer will develop and enhance ML-powered products focusing on models, metrics, pipelines, and collaboration with product teams.

Lead high-impact AI/ML projects in the automotive domain, overseeing technical strategy, project execution, and client management, while mentoring junior team members.

As a Machine Learning Engineer at Onyx, you will enhance agent and knowledge retrieval capabilities by implementing LLM-based graphs and advanced NLP algorithms, while collaborating with the team to improve user experience and product direction.

The Machine Learning Engineer will build data pipelines, manage multi-GPU training infrastructure, optimize code, and deploy inference pipelines for LLMs.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

Develop and deploy machine learning models for agentic workflows, optimize AI systems for multimodal applications, and innovate fine-tuning techniques.

The role involves developing and improving TTS/Voice Generation models, training, fine-tuning, evaluating speech models, and collaborating across research, engineering, and product teams in a fast-paced startup environment.

The Machine Learning Engineer designs and optimizes algorithms for data analysis and workflow automation, collaborating with engineering teams and ensuring algorithm performance on edge devices and high-performance environments.

The Machine Learning Engineer role involves optimizing models for performance, utilizing CUDA, GPU scheduling, and collaborating on ML systems design.

Lead the design of advanced AI systems for healthcare, develop evaluation frameworks, and drive LLM development while shaping AI strategy in a collaborative environment.

Seeking a Perception ML Engineer to develop and deploy advanced perception models for robotics, focusing on manipulation and navigation in dynamic environments.

The role involves developing and maintaining behavioral models for road users to enhance autonomous vehicle decision-making, collaborating with other teams and optimizing outputs for safety and effectiveness.