Bell Labs Generative AI Co-op

Description: Skyline Nav AI, Inc. is a well-funded, commercially successful scale-up focused on revolutionizing visual navigation technology as an alternative to GPS, for our commercial and military customers. We are seeking highly motivated and hungry recent graduates (Bachelor's/Master's/PhD's) who are passionate about computer vision, robotics and AI to join our team.

As a R&D Engineer, you will be responsible for developing and productionizing computer vision algorithms and machine learning models to help our technology achieve high-accuracy visual navigation. This includes developing new algorithms, as well as optimizing existing methods for real-time use on edge-devices.

Requirements:

1. Candidate must be a US citizen, eligible for US Department of Defense Security Clearance

2. B.S./M.S./Ph.D. degree in Computer Science, Electrical Engineering or related field

3. Strong programming skills in Python and C++

4. Proficient working with computer vision and machine learning concepts

5. Ability to work in fast-paced dynamic startup environment

Preferred:

- Experience with visual navigation or similar technologies

- Knowledge of drones and autonomous vehicle systems

We don't use automated chatbots to review applicants. Every applicant is reviewed by our leadership team. We typically get back to candidates within a few days of applying. 

If you are passionate about visual navigation and want to make an impact in this exciting and rapidly growing industry, we would love to hear from you. We offer competitive compensation packages, remote work and opportunities for growth within our company.

If you require any special accommodations to participate in this application process, please do not hesitate to email us at careers@skylinenav.com so we can assist you.

About Korl

Korl uses AI to automatically generate personalized, customer-specific presentations for critical business moments like QBRs (Quarterly Business reviews) and renewals. We're solving a real pain point by helping companies showcase their value to customers through data-driven, tailored content instead of generic templates. Our platform connects to tools like Salesforce, Jira, and Figma to build a holistic view of products and customers, then uses AI to craft compelling narratives.

Who We're Looking For

We're looking to hire passionate Computer Science students for full-time positions. We're seeking builders who are excited about:

• Designing and building scalable distributed systems and APIs.

• Working with cutting-edge AI/ML technologies (LLMs, agentic workflows).

• Tackling complex data integration and transformation challenges.

• Creating products that have an immediate, visible impact on customers.

What You'll Work On

We all contribute directly to core infrastructure and AI projects. Some of the more important projects and technologies:

• Centralized Data Access Service (CDAS): Build our unified data layer using Google Cloud Run, gRPC, and Protocol Buffers. You'll tackle challenging problems in schema versioning and data transformation, and create elegant abstractions for complex data models that serve as the backbone of our entire platform.

• Integration Platform: Design the systems that rapidly connect to external services (Salesforce, HubSpot, etc.) and normalize their data. This is a crucial, high-impact project for generating customer-specific insights at scale.

• AI-Powered Presentation Generation: Work with Large Language Models (LLMs) and agentic AI systems to automatically create tailored content. You'll handle large-scale data processing and build intelligent workflows that know precisely when to leverage AI versus when to rely on deterministic logic.

Why Join Korl?

• High-Impact Work: Work directly with experienced engineers on production systems serving real customers.

• Ship Fast: See your code ship quickly and make an immediate impact.

• Modern Tech Stack: Gain deep experience with Python, gRPC, Google Cloud, LLMs, and distributed systems.

• Small Team, Big Voice: Join a small, agile environment where your ideas and contributions truly matter.

Interesting Problems: Tackle fascinating challenges at the intersection of AI, data engineering, and product development.

Contact sumeet@korl.co if interested

Robotics R&D Intern – Large Behavior Models & Dual‑Arm Manipulation

(Spring/Summer 2026)

Location: Cambridge, MA — (In-person, MassRobotics). Duration: 12–16 weeks | Spring

(Jan–Apr, part-time available) and/or Summer (May–Aug, full-time) 2026

About IntuitiveMotion.AI

Born out of Harvard Business School and UT Austin’s renowned robotics community,

IntuitiveMotion.AI is building end‑to‑end manipulation systems that combine data‑efficient

classical robotics with emerging Large Behavior Model (LBM) methods. Our mission is to

unlock reliable, scalable automation for dynamic, human‑centric workspaces—beginning

in hospitality and adjacent verticals.

Why This Role Matters

In the next 12 months we will harden our software stack and expand from a single

customer pilot to several multi‑site deployments. Your research and engineering will

directly influence the robustness, adaptability, and scientific rigor of that scale‑up.

What You’ll Work On

• Hybrid Modeling Pipeline: Organize and expand our data pipelines, feeding

analytically generated trajectories into LBM pre‑training and richly annotated

tele‑op demonstrations into subsequent fine‑tuning—all within a unified, modular

framework.

• Demonstration Infrastructure: Strengthen and extend our existing tele‑operation

stack—improving latency, tactile feedback, and operator UX—while scaling data

ingestion and labeling pipelines.

• Simulation‑Based Testing & Validation: Build automated test harnesses in

simulation to stress‑test policies (robustness, regression, safety) and benchmark

performance under domain randomization before new hardware deployments

• System Reliability at Scale: Contribute to CI/CD, monitoring, and fault‑recovery

that will keep a fleet of robots productive and safe in production next year.Ideal Profile

• Currently pursuing a PhD or exceptional MS in Robotics, CS, EE

(Spring/Summer 2026 availability).

• Published or project experience in at least one: imitation learning, reinforcement

learning, manipulation, sim‑to‑real, or robotic perception.

• Proficient in Python/C++ and modern ML toolchains (PyTorch, JAX, or TensorFlow).

• Solid grasp of control theory, kinematics, and motion planning.

• Comfortable debugging on real hardware (ROS 2, MoveIt, NVIDIA Jetson/Orin, Dell

Aurora or similar).

Nice to Haves

• Experience with dual‑arm or mobile manipulation platforms.

• Statistical experiment design or MLOps background (e.g., A/B testing frameworks).

How to Apply

Send your résumé/CV plus links to any relevant papers or GitHub repos to

cecilia@intuitivemotion.ai with subject line “Robotics Intern 2026 – [Your Name]”.

Founding Software Engineer | Brace Health

Location: Cambridge, MA (In-person) Job Type: Full-Time

We’re building a new financial infrastructure of healthcare—reimagining how patients access coverage and how providers get paid. Our goal: reduce the cost of healthcare with purpose-built AI agents that streamline the billing maze so clinics can invest in care, not paperwork.

We’ve raised ~$4M from Bessemer Venture Partners (backers of Shopify, LinkedIn, and Toast), grown 10x in the last 60 days, and built a 6+ month customer waitlist with no sales/marketing.

We're now assembling a world-class founding engineering team. You’ll work alongside a technical founding team with backgrounds at Microsoft, Amazon, Meta, and Bain, and help shape the systems that power the future of healthcare.

What will you do:

● Core Systems Development: Build vertically integrated infrastructure that automates medical billing from end to end. Own mission-critical backend systems using Rust, Python, Kubernetes.

● AI-Driven Automation: Design and deploy production AI/ML systems that navigate complex payer rules and workflows. Work across LLMs, traditional ML, and multi-agent architectures.

● End-to-End Product Ownership: Build beautiful, high-performance frontend experiences with React, Remix, TypeScript. Collaborate directly with users to ship fast and improve constantly.

● Infrastructure & Reliability: Design for resilience, scale, and performance. Own our deployment stack across AWS, Kubernetes, and modern observability tools.

● Team & Culture: Join a small, elite team with high ownership. Help shape engineering culture, mentor peers, and lay the technical foundation for a category-defining company.

Who you are:

● A builder. You’ve owned and shipped complex systems in production, and you like to move fast without breaking things.

● Mission-driven. You care about building tools that improve people’s lives—and you’re energized by the chance to fix healthcare’s most painful problems.

● Gritty and curious. You learn quickly, ask good questions, and keep pushing until things work.

Our Stack:

● Rust for backend services: safe, fast, and reliable

● React + Remix + TypeScript for delightful user interfaces

● Python for AI/ML workflows

● AWS + Kubernetes for scalable infrastructure

● LLMs from OpenAI, Anthropic, Gemini, and open source

Why this matters:

Healthcare is the largest and most essential market in the world—but it’s riddled with complexity and inefficiency. Americans carry over $200B in medical debt, while providers spend $300B+ per year just trying to get reimbursed by insurance. The system is opaque, expensive, and broken—for both patients and doctors.

We believe this can be better. By rebuilding the billing layer with modern software and AI, we can unlock massive value: better access for patients, better economics for clinics, and less waste across the entire system.

Join Us: This is a rare opportunity to help architect foundational infrastructure in a trillion-dollar industry. If you're hungry to solve real problems, move fast, and build something that matters—we want to meet you

Link here to apply & learn more.

Member of the Technical Team - Create your own adventure

• We believe greatness can come from curiosity driven exploration. If you don’t
  find yourself aligned to one of the listed roles, but care about this
  problem, we want to hear from you too.

Preferences:

• Degree or experience in fields that may support leveraging AI/ML to make
  experimental science more reproducible, interpretable, and transferable at
  scale.

• Startup or early-stage experience preferred; comfort with ambiguity and rapid
  iteration is a must.

• Ideal candidates are located within commuting distance from Cambridge, MA.

Member of the Technical Team - Biomedical Scientist

What you’ll accomplish with us:

• Design, execute, and optimize experimental protocols across molecular and cellular biology domains with a focus on reproducibility and transferability and integration with AI ML models.

• Partner with our AI/ML and software teams to generate high-quality, structured data from experimental workflows—including edge cases and failure modes—that inform product design.

• Identify critical variables and hidden steps in experimental workflows, documenting processes in a way that enables robust handoff to humans and machines alike.

• Collaborate with internal R&D teams to scale and stress-test protocols across different lab environments, automation platforms, and execution conditions.

• Support customer deployments by embedding into partner labs, piloting new workflows, troubleshooting edge cases, and capturing lessons learned.

• Act as a bridge between the field and our product/engineering teams, articulating real-world constraints and needs to shape the development of tools and infrastructure.

• Develop and maintain experimental benchmarking frameworks to validate reproducibility, accuracy, and scalability across lab settings.

• Play a key role in shaping how we operationalize the capture of tacit biological know-how—from protocol intent to executional nuance.

• Become customer obsessed. Initiate, support, and lead program execution with external partners and collaborators to capture, document, and deliver results.

• Stay on top of the latest research in biomedicine and life sciences with an eye to integrate ML/AI and evaluate its applicability to our platform. We will support opportunities to publish or present where appropriate to establish technical leadership.

Requirements:

• PhD or advanced degree in Molecular Biology, Bioengineering, Computational Biology, or a related field.

• Demonstrated hands-on lab experience (industry or academic) with modern wet lab techniques including cell culture, protein engineering, and/or automation.

• Familiarity with digital lab tools (e.g., ELNs, LIMS, lab automation systems) and a desire to improve scientific workflows.

• Exceptional experimental design skills with a strong bias toward documentation, reproducibility, and iteration.

• Ability to troubleshoot protocols systematically, with attention to both technical detail and human variability.

• Ability to clearly communicate technical concepts to cross-functional teams and collaborate on projects spanning AI, biology, and product.

• Located within commuting distance from Cambridge, MA.

Additional preferences:

• Experience working with or supporting internal lab teams as well as direct customer-facing work in partner or external lab environments.

• Startup or early-stage experience preferred; comfort with ambiguity and rapid iteration is a must.

• Demonstrated experience using AI/ML tools in research, whether for experimental design, data analysis, or predictive modeling.

Member of the Technical Team - AI/ML Software Engineer

What you’ll accomplish with us:

• Develop end-to-end AI and software systems that enable reproducible and transferable science at scale.

• Design and implement multimodal data pipelines (for both pre-training and reinforcement learning).

• Collaborate closely with scientists and engineers across teams to drive alignment and ensure knowledge flows efficiently.

• Bring cross-functional initiatives from concept to delivery. Establish milestones, communication cadences, and decision-making frameworks.

• Become customer obsessed. Initiate, support, and lead program execution with external partners and collaborators to capture, document, and deliver results.

• Develop intuitive, usable tools and UIs in partnership with product and design to support scientist workflows.

• Evaluate and integrate external tools, open-source models, and strategic partners.

• Work alongside the biology and operations teams to identify automation opportunities and improve experiment documentation and reproducibility.

Requirements:

• Strong programming expertise, with experience in software engineering, data systems, machine learning, and/or AI product and model development.

• Fluency in Python, modern ML libraries (e.g., PyTorch), and cloud infrastructure (e.g., AWS, GCP)

• Demonstrated ability to turn ideas into functional prototypes. Ability to build quickly, test often, and refine thoughtfully—balancing prototypes with production quality as the company scales.

Additional preferences:

• PhD or advanced degree in Machine Learning, Computer Science, or related field.

• Experience in software engineering, data systems, machine learning, or AI product development in a scientific settings (either academic or industry)

• Experience building AI/ML-powered products from ideation to deployment

• Startup or early-stage experience preferred; comfort with ambiguity and rapid iteration is a must.

• Ability to clearly communicate technical concepts to cross-functional teams and collaborate on projects spanning AI, biology, and product.

• Ideal candidates are located within commuting distance from Cambridge, MA.

Member of the Technical Team - AI/ML Scientist

What you’ll accomplish with us:

• Design and implement novel machine learning approaches—especially in pre-training, multimodal learning, and reinforcement learning—to make experimental science more reproducible, interpretable, and transferable at scale.

• Design and develop AI models that can learn from experimental protocols, lab execution data, and failure modes to suggest, simulate, or guide future experiments.

• Develop and implement data collection strategies—including computer vision, audio, and sensor-driven interfaces—to capture tacit knowledge embedded in physical lab workflows and human decision-making.

• Become customer obsessed. Initiate, support, and lead program execution with external partners and collaborators to capture, document, and deliver results.

• Develop and test internal and external benchmarks, validation strategies, and frameworks for testing reproducibility, robustness, and scientific utility.

• Work alongside the biology and operations teams to identify automation opportunities, uncover latent structures in messy lab data, capture tacit knowledge, and improve experiment documentation and reproducibility.

• Translate scientific hypotheses into computational experiments, analyzing model behavior and experimental results to draw actionable insights.

• Stay on top of the latest research in ML/AI and evaluate its applicability to our platform. We will support opportunities to publish or present where appropriate to establish technical leadership.

Requirements:

• Advanced degree in Computer Science, Machine Learning, or a related field.

• Deep expertise in generative models, representation learning, multimodal learning, reinforcement learning, and/or causal inference.

• Fluency in Python, modern ML libraries (e.g., PyTorch), and cloud infrastructure (e.g., AWS, GCP)

• Demonstrated ability to design and implement ML models in noisy, complex, real-world settings—ideally involving biological or scientific data.

Additional preferences:

• Experience in a scientific or research-intensive environment—academic labs, biotech R&D, national labs, or similar.

• Familiarity with experimental workflows, lab automation, or scientific instrumentation.

• Startup or early-stage experience preferred; comfort with ambiguity and rapid iteration is a must.

• Ability to clearly communicate technical concepts to cross-functional teams and collaborate on projects spanning AI, biology, and product.

• Ideal candidates are located within commuting distance from Cambridge, MA.