Top AI & Machine Learning Jobs

Create challenging, expert-level questions about animals and pets in Brazilian Portuguese, write ideal responses, and decompose them into cited facts with sources and relevance. This remote freelance engagement supports AI training-data development, requires PhD-level expertise, and involves approximately 60 flexible hours over two months. Contributors use consumer-grade LLMs for research support and prompt-difficulty calibration while producing original content.

Develop and productionize machine learning models and predictive analytics using Python, Databricks, PySpark, SQL, and Delta Lake. Build scalable data science workflows, resolve healthcare data quality and entity-resolution issues, and apply Master Data Management practices. Partner with engineering, product, analytics, and business teams to deliver governed, HIPAA-compliant solutions. Perform exploratory analysis, feature engineering, model evaluation, deployment, documentation, and data lineage management for healthcare and member engagement initiatives.

Conduct research at the intersection of mechanistic interpretability and reinforcement learning. Develop methods to analyze language-model and agent internals, derive intrinsic rewards and training signals, run experiments, evaluate failure modes, and build reproducible research infrastructure. The fellow will own a focused project, collaborate with technical staff, communicate findings, and contribute to publications.

Deploys and operationalizes agentic AI coding tools for financial-services clients. The role combines software engineering, client advisory, AI workflow development, CI/CD and cloud integration, security and governance compliance, pilot measurement, production rollout, and developer training. Engineers configure Devin or Claude Code, build custom agent workflows and integrations, validate generated code, and modernize legacy systems while working with technical and executive stakeholders.

Leads and mentors junior developers while designing, modifying, testing, and deploying data solutions in Palantir Foundry. Builds data models and reports from ERP and legacy systems, translates business requirements into technical capabilities, and supports IT modernization. Requires Python, PySpark, cloud architecture, CI/CD, database design, Army domain knowledge, and an active DoD Secret clearance.

Develop and deploy perception, generative AI, and online mapping algorithms for L4 autonomous trucks. Responsibilities include building robust real-time software for safety-critical systems, integrating maps and vehicle sensors, improving mapping performance, leading features from concept through delivery, and coordinating stakeholders. The role requires deep learning model development and deployment, applied research, machine learning algorithm design, Python, and C++, with sensor fusion or online mapping experience preferred.

Develop and maintain high-impact software features across the full stack while integrating AI tools throughout architecture, coding, testing, debugging, and delivery. Architect AWS-based systems, build AI and MCP capabilities, guide engineering practices, review code, improve application quality and security, troubleshoot complex defects, and influence technical direction. The role requires deep C#/.NET, SQL, AWS, architecture, security, CI/CD, and distributed systems expertise, with independent ownership of ambiguous, high-impact initiatives.

Define and build an enterprise AI platform supporting LLMs, agentic workflows, intelligent automation, and cloud-native applications. Design scalable GCP architectures, microservices, event-driven systems, APIs, and automated CI/CD pipelines. Establish standards for AI governance, security, evaluation, observability, and operational excellence. Provide technical leadership and architecture guidance across engineering teams while remaining hands-on with implementation and enabling reusable platform capabilities.

Develop and implement statistical and machine learning trading strategies and quantitative models. Design optimization algorithms for portfolio construction and explore new research opportunities within derivatives and market behavior.

Design and build backend systems for AI agent orchestration, tool execution, workflow management, memory, and state handling. Develop scalable APIs and reliable infrastructure for distributed AI workflows, improve platform reliability and observability, and partner with product, research, and engineering teams to deliver agent capabilities. Own technical initiatives from architecture through production, maintain software quality through testing and continuous delivery, and mentor engineers on backend and distributed-systems practices.