Work on a feature platform that supports batch and real-time feature computation, training set generation, and feature lifecycle management for Ads ML. Requires ~3+ years in data/platform or ML infrastructure engineering, experience building production services and data pipelines, and familiarity with distributed systems such as Spark, Kafka, Airflow, Kubernetes, or BigQuery.

Seeking a Machine Learning Systems Engineer to design and implement large-scale data infrastructure and platforms that power Ads ML feature and training-set workflows. Responsibilities include building batch and realtime feature systems, feature governance (lineage, validation, drift detection, monitoring, reproducibility/versioning), integration with ML production systems, and improving observability, reliability, and cost efficiency. Requires 3+ years in data infrastructure/platform or ML infrastructure, hands-on experience with production services, data pipelines or workflow systems, and experience with at least one distributed system such as Spark/PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, or BigQuery.

Lead technical design and deployment of AI/ML solutions for NVIDIA GeForce NOW, including real-time diagnostics, LLM chatbot, forecasting, constraint-optimized capacity allocation, anomaly detection, retention modeling and large-scale production analytics. Requires extensive software and data science experience and hands-on experience with tools such as Python, Spark, Databricks, MLflow, Kubernetes and related MLOps technologies.

Lead and grow an ML-engineering/systems team focused on model optimization, training and inference efficiency, GPU enablement, profiling, benchmarking, load testing, observability, cost analysis, and efficiency certification. Partner with ranking, ML Platform, and serving teams to deliver measurable reductions in training time, latency, and serving cost. Requires deep ML engineering experience, distributed-systems fluency, and strong managerial skills. Base salary range (US): $230,000–$322,000 USD.

Coinbase is hiring an IC4 Machine Learning Engineer (remote - India) to build and improve an orchestration layer coordinating vendor and internal LLMs and human participants. The role requires 2+ years of professional ML/software engineering experience, strong Python skills, hands-on experience with LLMs/deep learning, and familiarity with tools such as LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock. Responsibilities include designing and shipping production-grade ML services, system design, and ensuring security and compliance.

Lead high-impact data science work across product data science and fair play at Chess.com. Responsibilities include building algorithms and models (including anomaly detection for cheating), partnering with product and engineering, managing and mentoring a team, and communicating results to technical and non-technical stakeholders. Role is full-time, 100% remote (work from anywhere) and asks for 5+ years of data science experience, strong Python and SQL, experience with BigQuery/GCP or similar, machine learning fundamentals, and familiarity with chess.

The Forward Deployed Engineer will work directly with enterprise clients to map and redesign workflows, establish operating models and governance, and deliver working AI-powered prototypes (using LLM APIs and low-/no-code tools). Requires 5+ years in management consulting or equivalent enterprise technology roles and experience driving organizational change, prototyping, and adoption strategies.

Hiring a Forward Deployed Engineer to map and redesign creative workflows, build and integrate AI-powered pipelines (LLMs, prompt engineering, agents) into DAM/CMS and marketing stacks, establish governance, and enable adoption. Role requires 5–10 years in creative technology, content operations, production engineering, or applied AI; 100% remote; compensation described as paid in USD.

Hands-on role configuring and implementing creative AI platforms, integrating AI workflows with DAMs, CMSs, marketing technology stacks, and project management systems. Requires 5+ years in creative technology, production engineering, content operations, or applied AI, and experience delivering production-ready solutions, proofs of concept, governance frameworks, and driving adoption within client teams.

Embedded, hands-on role that maps end-to-end creative workflows, redesigns processes, and implements AI-powered pipelines integrated with DAMs, CMSs, and marketing technology stacks. Responsible for building proofs of concept and production-ready solutions, establishing governance, enabling adoption, and tracking operational metrics. 100% remote role supporting engagements across Latin America and U.S. clients.

Hiring a Principal Software Engineer to lead development of vector search and vector database capabilities in Elasticsearch. The role involves designing and implementing vector search features, improving search relevance and performance, working with Lucene, contributing to open-source, and collaborating with a distributed engineering team. Strong Java, algorithms, and prior experience with vector similarity/HNSW/IVF and search platforms are emphasized.

Sardine seeks a Machine Learning Engineer to own model serving infrastructure, real-time inference, feature retrieval and deployment paths (bring-your-own-model support), monitoring, drift detection, retraining, and incident response. Role involves Python and Go work, Kubernetes/containers, GCP, CI/CD and infrastructure-as-code; roughly 20% hands-on modeling. Remote-first hiring across specified European countries.

Join Reddit’s ML Efficiency team to design and build systems, tooling, and optimization for ML training, evaluation, deployment, and operation at scale. Work areas include distributed training and serving, GPU and resource utilization, profiling and benchmarking, data pipelines, performance dashboards, and cross-functional initiatives to reduce costs and accelerate experimentation. Role requires strong software engineering experience (5+ years), Python proficiency, and systems-language experience and knowledge of ML infrastructure and performance engineering.

Join Reddit's ML Efficiency team to design and build systems, tooling, and optimizations that improve ML training and inference efficiency at scale. Responsibilities include improving GPU and resource utilization, developing profiling/debugging tools, optimizing distributed training and serving, building benchmarking frameworks and dashboards, and leading cross-functional initiatives. Requires BS/MS/PhD in CS or related field, 5+ years of software engineering experience, strong Python proficiency, and experience with distributed systems and ML infrastructure.

Lead technical direction and hands-on development (approx. 50% leadership/mentorship, 50% individual contributor) of content- and behavior-based embeddings and representation systems for ads, including multimodal embeddings, sequence models, knowledge-graph embeddings, and LLM/VLM-based representations. Requires 7+ years experience in end-to-end ML model lifecycle, strong background in content-rich NLP/CV at scale, familiarity with recommender/search/ads, and experience with frameworks such as PyTorch or TensorFlow.

The role leads technical strategy and execution for Ads Foundational Representations: building embeddings (text, media, knowledge graph, user intent) and related data and inference pipelines, working with LLMs/VLMs, and owning evaluation and experimentation. Requires 7+ years of ML lifecycle experience, staff-level technical leadership, strong experience with content-rich NLP/CV at scale, and familiarity with recommender/search/ads systems.

Mozilla is hiring a Senior Machine Learning Engineer to conceptualize, prototype, fine-tune, evaluate, and deploy LLM-driven user-facing features in Firefox. Responsibilities include applying RAG, summarization, classification, and intent modeling, using modern ML tooling (e.g., Hugging Face, LangChain, W&B, Ray), and collaborating with product and engineering teams with attention to privacy, latency, and usability. US salary ranges listed: $139,000–$218,000 USD per year depending on location tier.

Grafana Labs seeks a Staff Engineer (AI & Automation) based in Canada (remote, Quebec residents ineligible) to design, build, and operate multi-agent AI systems, LLM integrations, and backend services connecting models to internal and third-party data (BigQuery, CRMs, Slack). Requires 8+ years software engineering experience, 2+ years applying LLMs in production, strong Python and Node.js skills, and experience with GCP serverless/containerized services.

Twilio is hiring a remote-from-Spain Machine Learning Engineer for the Conversation Intelligence team. The role involves designing and engineering AI/ML features and end-to-end pipelines (data ingestion, feature engineering, model development, validation, deployment), instrumenting services with metrics and telemetry, participating in on-call rotations, and collaborating on product and technical design. Required: 2+ years ML engineering/applied ML experience, proficiency in Python and at least one ML framework (PyTorch, TensorFlow, or JAX), familiarity with NLP libraries (Hugging Face, NLTK, spaCy), and experience with cloud-based infrastructure (AWS/GCP/Azure).

Twilio seeks a Machine Learning Engineer to design, implement, and operate end-to-end ML solutions for Conversation Intelligence. The role involves building data pipelines, training and validating models, deploying inference services at scale, instrumenting telemetry, and participating in on-call rotations. Required: 2+ years relevant experience, proficiency in Python and at least one ML framework (PyTorch, TensorFlow, or JAX), and familiarity with NLP libraries and cloud infrastructure.