Lead the design and delivery of full-stack internal AI applications that incorporate LLMs, agents, retrieval systems, workflow automation, enterprise integrations, and application-level identity/authorization. Partner with platform and business teams to instrument telemetry, ensure security and compliance, and convert prototypes into repeatable, production workflows. Requires 7+ years software engineering experience.

Embed with enterprise customers to prototype and productionize AI and agentic use cases on Cloudera. Responsibilities include developing full‑stack ML applications, advising on AI roadmaps and deployments, standardizing patterns into reference architectures and playbooks, and channeling field feedback to product teams. Requires 7+ years building and deploying production systems and 2–4 years specifically on ML/GenAI or agentic applications; familiarity with MLOps, LLM tooling (e.g., LangChain, LlamaIndex, vLLM), vector databases and RAG, and distributed data platforms (Apache Spark, Iceberg, Kubernetes).

As an MLOps Engineer you will design and evolve production ML lifecycle systems (experiment tracking, artifact management, versioning, lineage, promotion workflows), build operational infrastructure for LLM/agentic systems, design evaluation and monitoring frameworks, and build large-scale training pipelines. Role requires 5+ years of software/MLOps/ML platform engineering experience, strong Python engineering, and experience with platforms like Databricks, Spark, Delta Lake and MLOps frameworks such as MLflow/Metaflow/Kubeflow.

Lead development of core platforms that process large volumes of network and operational data to power AI experiences and agentic systems. Responsibilities include architecture and hands-on implementation of distributed, real-time, cloud-native microservices and data pipelines, mentoring engineers, and ensuring reliability, observability, and security for production deployments.

Join the Observability, Monitoring, and Integrations team within GitLab's Monetization org to design, build, and operate telemetry, monitoring, and automated anomaly detection for billing and usage pipelines across CustomersDot, Salesforce, and Zuora. Role emphasizes Prometheus/Grafana/OpenTelemetry, SLOs/SLIs, runbooks, incident handling, reconciliation, and exploring AI/ML techniques. Open at Senior and Staff levels. Remote role with a Bangalore location listed.

Udacity (an Accenture company) is hiring external contractors as technical mentors for Claude/Anthropic AI topics. The role is remote across multiple timezones and requires 5+ years of relevant technical experience and expertise in the Claude ecosystem (Claude API, Claude Code, Claude Agent SDK, MCP), agentic AI, prompt/context engineering, Python, REST/JSON, system architecture, CI/CD, SQL and production AI workflows. Responsibilities include 1:1 mentoring calls, technical deep-dive sessions, and group Q&A. US applicants must have work authorization that does not require visa sponsorship.

Lead Tide's Ongoing Monitoring machine learning function: define risk engineering strategy, build and scale production risk and fraud infrastructure, develop self-service tooling for internal teams, and ensure compliance with regulatory standards. Requires senior leadership experience (~12+ years), deep fintech risk/compliance expertise (AML, KYC/KYB), ML and adversarial-AI experience, and cloud-native engineering background.

Individual Contributor Staff Data Scientist to design and deploy predictive ML models for fraud and risk, address highly imbalanced datasets and data/concept drift, build production GenAI/Agentic AI workflows, collaborate with engineers and product teams, and act as the team SME. Requires 10+ years' experience in data science/ML and strong applied skills in classical ML, production ML engineering, Python/SQL, and cloud (AWS or GCP).

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 ownership of end-to-end evaluation and benchmarking infrastructure and domain-specific post-training (SFT, RLHF, RLAIF, DPO) for foundation models. Responsibilities include designing task-level evals, building comparative benchmark pipelines, synthetic data generation, CI-integrated regression suites, dataset curation, and conducting fine-tuning and ablation studies. Requires strong software engineering skills in Python and experience with PyTorch or JAX and distributed training.

Twilio is hiring Senior or Staff Applied Research Software Engineers to join an incubation team focused on rapid prototyping and emerging technologies. Responsibilities include developing, testing, and deploying prototypes and production-ready solutions, collaborating on AI/ML experiments, participating in code reviews, and communicating technical progress. Required skills include proficiency in languages such as JavaScript, Python, or Java; experience with front-end (React/Angular) and/or back-end (Node.js/Springboot) frameworks; and database familiarity (SQL or NoSQL). Role is remote and must be based in India.

Senior ML Engineer responsible for designing and deploying an orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks. Build production-grade Python ML services, lead end-to-end ML projects, establish system and coding best practices, and mentor engineers. Requires 5+ years experience and hands-on work with LLMs/generative AI and frameworks such as LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock. Annual base salary listed as ₹6,612,600 INR.

Technical software engineering role within Data Science focused on building production multi-agent systems, AI-powered security chatbots, and applied LLM workflows for security operations (alert triage, summarization, automation). Role expects 8+ years of professional software engineering experience, 1–2 years hands-on applied AI building multi-agent/chatbot or tool-using agent systems, expertise in .NET/TypeScript/Python, familiarity with cloud AI services (AWS Bedrock preferred) and LLM SDKs, and strong emphasis on evaluation, reliability, and AI security practices.

Join Augury's AgenticAI team to own end-to-end ML systems—problem scoping, data pipelines, model development, deployment, and production monitoring. Work combines time-series modeling, signal processing, classical ML, deep learning, and generative AI (LLMs, embeddings, agent architectures) to deliver customer-facing industrial AI solutions.

Lead end-to-end development of GenAI and AgenticAI applications for industrial manufacturing, including prototyping, production deployment, monitoring, and evaluation. Build LLM-powered workflows (RAG, prompting, embeddings, tool calling, orchestration), integrate sensor time-series and unstructured data, and develop backend services in Python (REST/gRPC). Collaborate with Product, Engineering, and Applied AI teams; required ~2–4 years of relevant experience and familiarity with GenAI frameworks (e.g., LangChain, CrewAI, AutoGen), MLOps/LLMOps tooling, and observability platforms.

Hands-on technical lead reporting to Director, Enterprise AI. Own end-to-end AI initiatives from discovery through deployment, focusing on practical prototypes, integration with existing systems (APIs, orchestration tools, GitLab Duo Agent Platform), measuring business and flow metrics, and ensuring safety/guardrails. Strong coding skills (Python or JavaScript/TypeScript), LLM and prompt-engineering expertise, systems thinking, and familiarity with enterprise systems (Salesforce, Marketo, Zendesk) are required.

Senior role within Tide’s Ongoing Monitoring team focused on designing and implementing behaviour-based AML monitoring controls and member segmentation. Responsibilities include building and optimising models, translating AML typologies into data-driven logic, maintaining audit-ready model documentation, and communicating technical trade-offs to stakeholders. Requires a minimum of 4 years in data analytics, strong SQL and Python skills (Pandas, PySpark), and experience with statistical and optimisation methods in a financial crime or risk context.

Twilio is hiring a Senior Manager, Machine Learning (remote, based in India) to lead and hands-on contribute to the Conversation Memory team. The role requires 10+ years in applied ML/AI with experience leading ML teams and building production-grade ML/LLM systems (including orchestration, embeddings, vector stores, and MLOps). Responsibilities include technical leadership, team hiring and development, roadmap definition, experimentation, deployment, and cross-functional collaboration.

Udacity (an Accenture company) seeks external part-time AI Technical Mentors to provide 1:1 sessions, technical deep-dives, and group Q&A. Mandatory skills include Python, API integration, core AI/ML concepts, familiarity with LLMs and generative AI, prompt engineering, ML libraries (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow), exposure to frameworks like LangChain and LlamaIndex, and knowledge of RAG, embeddings, and vector databases.

Contractor mentor role supporting learners in Udacity's School of Data. Requires 5+ years of relevant technical experience and proficiency in Python and/or SQL, data analysis and modeling, ETL and data pipelines, data visualization tools (e.g., Pandas, NumPy, Tableau/Power BI), and familiarity with databases and data warehousing. Responsibilities include 1:1 mentoring, technical deep-dive presentations, and group Q&A sessions.