Top Senior Machine Learning Jobs

Design, deploy, and maintain large-scale ML workflows and knowledge graph services. Build production-ready LLM and RAG-based search pipelines, data ingestion/preprocessing, feature stores, monitoring, and security. Collaborate with cross-functional teams, document systems, research advanced ML/NLP techniques, optimize knowledge graph algorithms, and mentor junior engineers.

Design, build, and productionize personalized recommendation models and LLM-based experiences for Spotify's Home feed. Own model training, fine-tuning, evaluation, A/B testing, inference optimization, and ML platform/data pipeline improvements. Drive technical direction, mentor engineers, and collaborate with cross-functional partners to deliver scalable, cost-efficient personalization at global scale.

Lead development and production deployment of ML products: perform exploratory analysis, build and evaluate models, design experiments and metrics, leverage generative AI and graph-based methods, collaborate with product and engineering, influence strategy, and maintain robust CI/CD and platform practices.

Senior Machine Learning Engineers will develop ML products and lead projects end-to-end—from initial concept through final launch—across S32 portfolio companies. Candidates should drive product direction, have strong ML engineering and productization experience, and make significant business impact.

As a Senior Machine Learning Scientist, you will develop multimodal foundation models using large-scale single-cell datasets to advance drug discovery, applying deep learning methods and collaborating with biologists and engineers.

As a Machine Learning Scientist at Nucs AI, you will develop innovative ML methods for medical image analysis, collaborate with clinicians, and contribute to clinical validation studies, impacting cancer diagnostics.

Lead architecture and productionization of scalable ML/LLM systems for legal products. Build LLM applications (RAG, agents), hybrid search, APIs, streaming/data pipelines, containerized deployments, and observability. Partner with data scientists to turn models into reliable, low-latency customer-facing services and establish reusable frameworks, best practices, and technical leadership across teams.

Develop and deploy machine learning solutions for autonomous truck applications: EDA, deep learning model development, embedded deployment, data ingestion/curation, analytics, visualization, technical leadership, and process improvement across manufacturing and business domains.

Lead post-training for LLMs (CPT, SFT, RL) focusing on RL methods; design and curate training and reward data; run and debug distributed training on mid-to-large GPU clusters; build evaluation and verifier pipelines; partner with product and business teams to deliver targeted model improvements quickly.

Build and design backend services, AI agents, and machine learning models. Collaborate cross-functionally to deliver AI features and maintain code quality.

The Senior Machine Learning Engineer will lead the perception stack, focusing on detection, tracking, classification, and sensor fusion for targeting systems, with responsibilities including model development and real-time optimization on embedded devices.

Build and improve AI/ML systems and data pipelines for a B2B SaaS platform; shape product and technical strategy; work with customers; mentor team members; ensure secure, robust, and scalable infrastructure.

As a Senior Software Engineer, you'll develop machine learning models and software applications, translating technical requirements into solutions while ensuring excellence in product delivery.