This is a remote position.
We are seeking a dynamic AI Engineer to help design and deploy cutting-edge artificial intelligence systems that drive innovation and automation across our platforms. This role bridges the gap between data science and software engineering, requiring expertise in developing, integrating, and optimizing AI-powered solutions.
Design and develop AI systems and intelligent applications, leveraging deep learning, NLP, and computer vision.
Collaborate with cross-functional teams to identify business problems solvable through AI.
Build production-ready APIs that expose AI capabilities across platforms.
Integrate AI solutions into mobile, web, or enterprise software stacks.
Research and experiment with generative AI (LLMs, GANs), reinforcement learning, and other advanced techniques.
Optimize inference performance and latency using quantization, pruning, or ONNX.
Maintain AI systems through continuous evaluation, retraining, and performance tuning.
Develop reusable AI components and tools that accelerate engineering velocity.
Requirements
Bachelor’s or Master’s degree in Computer Science, AI, Electrical Engineering, or related discipline.
3–6+ years of experience delivering AI/ML models into production systems.
Strong programming skills in Python and familiarity with C++, Java, or Go.
Proficiency with AI/ML libraries like TensorFlow, PyTorch, Hugging Face Transformers, OpenCV.
Experience building RESTful APIs and microservices that expose AI logic.
Familiarity with AI model lifecycle tools like MLflow, Triton Inference Server, ONNX Runtime.
Experience deploying AI solutions to cloud platforms (Azure, AWS, GCP).
Experience with LLMs (e.g., GPT-3/4, Claude, Mistral) and prompt engineering.
Familiarity with vector databases (Pinecone, Weaviate) and RAG systems.
Hands-on experience with AI infrastructure tools (NVIDIA Triton, Ray, or DeepSpeed).
AI-related certifications or contributions to open-source AI projects.
Similar Jobs
What you need to know about the Boston Tech Scene
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
