Top AI & Machine Learning Jobs

Designs secure, scalable cloud-enabled architectures for government and Marine Corps modernization initiatives. Partners with customers, engineers, and stakeholders to translate mission needs into technical solutions across AI/ML, data, cloud, DevSecOps, and legacy systems. Builds agentic AI pipelines using frameworks such as LangChain and LlamaIndex, fine-tunes large language models, integrates code-as-data techniques, evaluates technical risks, and guides implementation.

The Senior Data Scientist will develop advanced statistical, predictive, and prescriptive models to solve enterprise business challenges. Responsibilities include analyzing diverse data sources, building scalable analytics solutions with Python, SQL, cloud platforms, and visualization tools, translating findings into executive recommendations, and supporting strategic decision-making. The role also leads AI and machine learning initiatives, cross-functional projects, analytics strategy, and mentoring of junior data science team members.

Serves as a hands-on technical lead building, deploying, and operating governed agentic AI and LLM solutions on Databricks. Develops RAG and multi-agent systems, MCP integrations, secure tools, prompt and context engineering, AI Gateway controls, identity authorization, observability, CI/CD, testing, and monitoring. Partners with business, security, risk, compliance, and data teams to deliver measurable outcomes in a regulated banking environment, while establishing governance standards and mentoring engineers.

Develops and evaluates AI-powered software, automation scripts, prototypes, and enterprise solutions using programming languages, LLMs, APIs, and AI-assisted coding tools. Collaborates with engineers, architects, and business development teams on technical research, federal proposals, workflow automation, and solution documentation. The role also assesses AI-generated code for quality, security, performance, and maintainability while supporting adoption of approved AI technologies.

Design and build Uber’s large-scale machine learning training infrastructure, addressing challenges involving massive datasets, models, distributed systems, and GPU resources. Mentor engineers, establish technical standards, review architectures and code, optimize performance and utilization through statistical analysis, and develop tools that improve engineering velocity. Lead complex projects from inception through global productionization while coordinating with Product, Data Science, and Operations teams.

Develop and deploy computer vision and machine learning solutions for autonomous vehicle perception, including object and signal recognition. Build production software in Python and C++, integrate models with vehicle systems, process camera and LiDAR data, and create testing and evaluation tools. Train, optimize, and analyze AI models, debug algorithms, improve inference performance, and research emerging technologies for safer autonomous driving systems.

Build and operate production AI infrastructure for multi-agent systems across customer clouds. Develop Python or Go tooling, CLIs, controllers, and services; deploy and optimize LLM inference with Kubernetes and vLLM; manage MLOps, model releases, observability, CI/CD, GitOps, security, and multi-cloud platform reliability. The role also involves Kubernetes operators, Terraform, GPU scheduling, agent runtimes, evaluation pipelines, and developer self-service automation.

Lead full-stack development of agentic AI workflows and a payroll platform using React, TypeScript, .NET, event-driven systems, and Azure. Design secure, scalable architectures; supervise AI-generated code; establish prompts, evaluations, guardrails, and testing practices; deliver frontend and backend features; own automated unit, integration, and end-to-end testing; and mentor engineers while influencing technical direction and business outcomes.

Designs, develops, and maintains AI-enabled business system solutions, automation pipelines, enterprise integrations, analytics, and reusable application components. Partners with stakeholders and platform owners to translate business needs into secure, scalable solutions across Oracle, Salesforce, Foundry, and low-code platforms. Supports AI governance, data protection, compliance, data lineage, architecture, documentation, and operational procedures.

Build and optimize AI agents, automated workflows, and marketing technology integrations that support demand generation, outbound prospecting, campaign execution, pipeline growth, and marketing operations. The role involves connecting Salesforce, HubSpot, product, customer, and CRM data; evaluating emerging AI technologies; and implementing monitoring, safeguards, testing, and feedback loops to ensure reliable, measurable business outcomes.