10,680 AI Engineers jobs in the United States

About the job AI Data Engineers

AI Data Engineers
Compensation: $170,000 - $222,000 + competitive equity
Location: Remote (US-based only) | Visa sponsorship not available
Hiring timeline: ASAP | Hiring 3 engineers

Who Are We?

Were a fast-growing startup tackling one of the most critical and underserved problems in AI: access to high-quality training data. In industries like healthcare and media, the process of sourcing and preparing data is complex, expensive, and often unreliable. Our platform enables the secure, efficient, and privacy-centric exchange of training data, helping some of the worlds most ambitious AI companies build smarter models, faster.

With a small but mighty team (18 and counting), recent funding, and a sharp focus on impact, were building the infrastructure that could define the future of AI.

What's In It for You?

• A front-row seat at one of the most strategically important problems in AI
• Meaningful equity and competitive compensation
• The chance to work on technically rich challenges involving unstructured data (PDFs, videos, medical imaging, and more)
• Autonomy to lead projects from vague requirements to structured outcomes
• Remote-first environment with highly motivated teammates from diverse backgrounds

• Architect and implement scalable, automatable data pipelines with strong emphasis on validation, transformation, and compliance
• Optimize storage and retrieval layers to reduce cost and boost performance across the platform
• Extract, process, and transform unique data types think clinical notes, video metadata, diagnostic imaging
• Collaborate with a small but highly effective engineering team to scale infrastructure and deliver product impact
• Work cross-functionally to support AI and product use cases in healthcare and media

• 5+ years of experience in data engineering, ideally including startup environments
• Fluency with Python and/or Java in production-grade systems
• Experience with modern data infrastructure, orchestration tools, and working with big data in real-world environments
• Comfort working independently on projects with limited specability to define and execute end-to-end
• Bonus: experience with data privacy, healthcare compliance (HIPAA, etc.), or media data pipelines

• Develop and implement AI solutions such as Retrieval-Augmented Generation (RAG) and Agentic Workflows using advanced techniques in prompt engineering and fine-tuning of Large Language Models (LLMs).
• Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities.

• Design and develop machine learning models and algorithms to address business challenges and improve product features.
• Deploy machine learning models in production environments to ensure scalability and efficiency.
• Optimize and refine models based on performance metrics and feedback.

• Collect, clean, and preprocess data from various sources to create robust datasets for training and evaluation.
• Implement data augmentation and feature engineering techniques to enhance model performance.
• Maintain and manage data pipelines to ensure seamless data flow and integration.

• Develop scalable APIs in python (fastApi, Apache, Gunicorn) for model inferencing

• Work closely with software engineers, data scientists, and product managers to align AI/ML initiatives with business goals.
• Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner.
• Provide mentorship and guidance to junior team members and contribute to the upskilling of the team.

• Bachelor's or Master's degree in computer science, Statistics, Data Science, or a related field.
• 6+ years of experience in Machine Learning and Data Science.
• Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods, data structures, and algorithms.
• Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs.
• Experience developing and deploying AI solutions on cloud platforms (e.g., AWS, Azure, or GCP).
• Experience in building Asynchronous Python APIs.
• Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions.
• Proven experience in developing and deploying machine learning models in a production environment.
• Experience working with large datasets and performing data analysis.
• Passion for learning and staying up-to-date with the latest advancements in AI field

• Develop and implement AI solutions such as Retrieval-Augmented Generation (RAG) and Agentic Workflows using advanced techniques in prompt engineering and fine-tuning of Large Language Models (LLMs).
• Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities.

• Design and develop machine learning models and algorithms to address business challenges and improve product features.
• Deploy machine learning models in production environments to ensure scalability and efficiency.
• Optimize and refine models based on performance metrics and feedback.

• Collect, clean, and preprocess data from various sources to create robust datasets for training and evaluation.
• Implement data augmentation and feature engineering techniques to enhance model performance.
• Maintain and manage data pipelines to ensure seamless data flow and integration.

• Develop scalable APIs in python (fastApi, Apache, Gunicorn) for model inferencing

• Work closely with software engineers, data scientists, and product managers to align AI/ML initiatives with business goals.
• Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner.
• Provide mentorship and guidance to junior team members and contribute to the upskilling of the team.

• Bachelor's or Master's degree in computer science, Statistics, Data Science, or a related field.
• 6+ years of experience in Machine Learning and Data Science.
• Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods, data structures, and algorithms.
• Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs.
• Experience developing and deploying AI solutions on cloud platforms (e.g., AWS, Azure, or GCP).
• Experience in building Asynchronous Python APIs.
• Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions.
• Proven experience in developing and deploying machine learning models in a production environment.
• Experience working with large datasets and performing data analysis.
• Passion for learning and staying up-to-date with the latest advancements in AI field

AI Cluster Network Engineers

Duration: 6 months possible CTH - no sponsorship available
Location: Hybrid Onsite in Morrisville, NC

Required Skills:
Must have:
• Experience with ND/NDFC for building and troubleshooting Networks
• Experience with VXLan based networks and troubleshooting
• Experience monitoring and troubleshooting QoS for RoCEv2
• Experience with BGP routing
• Experience with ACI
• Desirable to have experience with L3 Fabrics
• Desirable to have familiarity with Nvidia and Linux networking
• Desirable to have experience with Python, Prometheus and Grafana
• Desirable to have experience with FirePower Firwalls