Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Build deep learning models from scratch (custom transformer architectures) to detect fraud and account sharing at Adobe in Bangalore, owning the full ML lifecycle from feature engineering on Databricks/Spark through large-scale GPU training to production deployment and monitoring.
Senior Data Engineer building data pipelines, ETL jobs, and cloud data platforms (AWS/Azure) for consulting clients, using Python, Terraform, and GitLab.
Senior AI Engineer architecting and implementing agentic AI solutions for semiconductor manufacturing process control at KLA's Dresden office, working with Python, C/C++, PyTorch, and web front-end technologies.
Architect and implement agentic AI solutions—multi-agent systems, reinforcement learning, and web front-ends—for semiconductor manufacturing process control at KLA's Dresden Software Center of Excellence.
Lead Data Scientist designing, deploying, and monitoring ML/AI solutions (including NLP and GenAI) across Risk, Fraud, Marketing, and Portfolio Management in the payments and financial services space, using Python, SQL, and big data frameworks.
Data Scientist at FIS building and deploying predictive models and AI solutions across Risk, Fraud, Marketing, and Portfolio Management in financial services, using Python, SQL, and machine learning libraries.
Lead a team of five experienced data engineers building and operating Databricks-based data pipelines for a Fortune 500 analytics program, setting technical direction, engineering standards, and delivery practices.
Manage a team of Data Scientists at Sanofi's Commercial Data Science division in Toronto, leading the design and deployment of AI, ML, Generative AI, and Agentic AI solutions for commercial operations using Python, cloud platforms (AWS/GCP), and tools like Snowflake.
Senior Associate Data Scientist developing and deploying ML/forecasting models to support business decision-making at Amgen's Hyderabad office, using Python, SQL, and MLOps practices across the full model lifecycle.
Design and build cloud-native data platforms and pipelines to power Mastercard’s AI and Generative AI solutions, including feature stores, vector databases, and MLOps workflows.
The Senior Specialist, Data Science will design and maintain automated ELT pipelines using dbt Core and GCP, while managing infrastructure via Terraform and supporting MLOps initiatives. The role focuses on building scalable data architectures, optimizing BigQuery performance, and integrating enterprise data sources.
The MLOps Lead Engineer will design and automate end-to-end machine learning production lifecycles on the Databricks Lakehouse platform. This role involves leading technical implementations, managing CI/CD/CT pipelines, and providing governance and upskilling for client-side engineering teams.
The Senior Software Engineer will design, develop, and deploy AI/ML models and pipelines to improve operational efficiency within the aerospace and defense sector. The role involves working with Python, MLOps practices, and generative AI technologies in a hybrid work environment.
Technical Product Owner leading the strategy, roadmap, and delivery of digital products supporting toxicology workflows at J&J, integrating LIMS/ELN systems and collaborating across scientific and engineering teams.
The Technical Product Owner for Toxicology manages the technical strategy, roadmap, and delivery of digital platforms and models used by toxicology scientists. This role requires bridging scientific needs with technical execution, overseeing data engineering, and ensuring compliance in a drug discovery environment.
The Solution Architect will design and deploy AI environments, manage MLOps/LLMOps pipelines, and implement RAG systems across various infrastructure types. The role involves hands-on engineering, AI governance, and mentoring teams while collaborating with global stakeholders.
Design and implement GenAI and Agentic AI solutions across UOB's banking business units, translating AI platform capabilities into practical banking use cases while ensuring security, compliance, and value realization.
The AI Solutions Engineer designs, develops, and deploys AI and LLM solutions to solve business challenges. The role involves optimizing models, managing deployment pipelines, and collaborating with cross-functional teams using tools like Python, PyTorch, TensorFlow, and cloud AI services.
Lead the architecture and deployment of production-grade ML solutions for geospatial applications, focusing on Python-based model development, API services, and MLOps practices.
Builds and deploys ML models to improve underwriting profitability, automation, and efficiency for a Lloyd’s Syndicate, owning full lifecycle from problem framing to production, with Azure/MLOps focus.
We couldn't check your fit for this role — add a CV to your profile to see it next time.