Top Tech Jobs & Startup Jobs

Lead a small AI engineering team while remaining hands-on in research and production software development. Build agentic capabilities for monitoring, guardrailing, evaluation, collaboration, and security. Perform exploratory data analysis, feature engineering, model fine-tuning, prototyping, and technical design. Translate AI research into scalable product features, set technical direction, mentor engineers, and deliver reliable production code.

Develop and optimize generative AI architectures for material and molecular discovery, including diffusion models, flow matching, and GFlowNets. Integrate reward signals from learned predictors and simulations, manage data ingestion and quality control, develop computational workflows, and deploy production-grade ML capabilities. Collaborate with ML researchers, computational scientists, engineering, product, and R&D teams. The role requires expertise in applied ML, scalable frameworks, cloud platforms, and material discovery, with preferred experience in active learning, Bayesian optimization, guided generation, and agentic or LLM methods.

Build production agentic AI capabilities focused on monitoring, guardrails, evaluation, security, collaboration, and ROI. Perform machine learning tasks including exploratory data analysis, feature engineering, and model fine-tuning. Translate research into scalable software, rapidly prototype features, collaborate cross-functionally, and deliver production-ready code while exploring emerging agentic technologies and AI security techniques.

Build production-ready agentic AI capabilities focused on monitoring, guardrails, evaluation, security, quality, and human-agent collaboration. Perform machine learning tasks including exploratory data analysis, feature engineering, and model fine-tuning. Translate research into scalable software, rapidly prototype features, collaborate cross-functionally, and explore emerging agentic technologies.

Develop and deploy machine-learned interatomic potentials for PFAS substitution. Responsibilities include generating and curating first-principles training data, building reproducible cloud and HPC workflows, training and validating ML force fields, running molecular dynamics and quantum chemistry campaigns, predicting physical properties, extending models to condensed-phase and process chemistries, and communicating model uncertainty and domain limitations.

Lead a small team developing secure, reliable agentic AI capabilities. Responsibilities include setting technical direction, building agent monitoring, evaluation, and guardrail frameworks, performing machine learning tasks, translating research into production features, mentoring engineers, and contributing hands-on code and technical designs. The role focuses on agent collaboration, trust, security, quality measurement, and scalable software delivery.

Build production-ready agentic AI capabilities focused on monitoring, guardrails, evaluation, security, quality, and human-agent collaboration. Perform exploratory data analysis, feature engineering, and model fine-tuning; translate research into scalable software; prototype rapidly; and ship reliable code. The role requires strong AI/ML and software engineering expertise, Python skills, cross-functional collaboration, and interest in AI security, agent orchestration, red teaming, and secure model deployment.

Lead a small team developing secure, reliable agentic AI capabilities. Responsibilities include building agent monitoring, guardrails, evaluation frameworks, and collaboration tools; performing machine learning tasks such as exploratory data analysis, feature engineering, and fine-tuning; translating research into production features; contributing code and technical designs; and mentoring engineers while setting technical direction.

Designs and manages multi-cloud infrastructure across GCP, AWS, and Azure using Terraform and Kubernetes. Provides hands-on developer support, troubleshoots infrastructure and cluster issues, and maintains highly available systems. Responsibilities include networking, container orchestration, monitoring, logging, CI/CD automation, documentation, security collaboration, and on-call participation.

Own and negotiate complex commercial transactions, including customer agreements, research collaborations, partnerships, data licenses, SaaS contracts, vendor agreements, and professional services agreements. Partner with sales, science, finance, and R&D teams, particularly on life sciences and computational chemistry deals. Build scalable legal infrastructure through playbooks, templates, fallback positions, self-service processes, and AI-enabled contract workflows.