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Senior Computer Vision Engineer (2D or 3D – Clinical AI)

About the Company

The mission is simple but ambitious: democratize access to high?quality cardiac care, especially in regions where cardiologists and advanced imaging equipment are scarce.

About the Role

This is a hands-on applied engineering position focused on building and deploying real clinical AI, not academic experiments. You will own production imaging models end?to?end, ensure reliability across diverse clinical settings, and work closely with clinical, regulatory, and deployment teams.

Profile A –

• Segmentation
• Localization
• Ultrasound/Echo image processing
• Signal and noise?robust imaging pipelines

Profile B – 3D Modeling

• Volumetric reconstruction
• 3D geometry and physics-informed modeling
• Computational representations of cardiac structures

Exceptional candidates may be considered for both tracks.

What You Will Own

Computer Vision Development

• Build production-grade CV models used in live cardiac workflows
• Develop 2D segmentation, 3D/4D reconstruction, and mathematical modeling systems
• Optimize models for low?latency clinical deployment
• Debug imaging pipelines across noisy, highly variable datasets

Production ML & Deployment

• Own pipelines from prototype ? production
• Support deployment engineers with real?world constraints
• Maintain model reliability across multiple international regions
• Monitor drift, performance degradation, and operational issues

What We’re Looking For

Required

• Strong experience in Computer Vision (2D and/or 3D)
• Production ML experience-beyond research or academic prototypes
• Background in biomedical or clinical imaging (ultrasound strongly preferred)
• Ability to debug, iterate, and deliver under pressure
• Experience working with deployment or ops engineering teams
• Comfort writing regulatory?oriented technical documentation
• Strong Python + PyTorch skills
• Startup mindset – bias for action, adaptability, ownership

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Director of Cloud & Private Cloud Engineering

Overview

This role leads a large‑scale Cloud and Private Cloud Engineering organisation within a highly technical, engineering‑driven enterprise environment. The Director owns both private and public cloud platforms and is responsible for unifying previously siloed infrastructure efforts into a single, coherent cloud platform that supports enterprise and product workloads at scale.

The organisation is building much of its cloud platform from the ground up using modern, open‑source tooling. While strong technical capabilities already exist across engineering teams, this role exists to provide the strategic ownership, connective leadership, and execution focus needed to bring the platform together and drive real delivery.

The Organisation & Scope

• Lead an organisation of 50-100 engineers, including senior managers and directors
• Teams span SRE, DevOps, platform engineering, and cloud infrastructure
• Geographic footprint primarily across the US and India
• Responsible for both private cloud and public cloud environments

Role Responsibilities

• Own the end‑to‑end strategy and execution for private and public cloud platforms
• Unify fragmented cloud efforts into a single, integrated platform
• Drive execution – moving strategy and architecture into delivered, production‑ready systems
• Provide directional leadership to architects and senior engineers without acting as the primary architect
• Build trust, autonomy, and accountability across a large, established engineering organisation
• Oversee compute, GPU, storage, Kubernetes, and cloud infrastructure
• Maintain visibility into cost, reliability, scalability, and performance
• Partner across engineering, security, and enterprise IT stakeholders to enable adoption

Why This Role Exists

The organisation has strong technical depth, but cloud capabilities are currently developed in pockets. Public cloud usage is progressing well, Kubernetes is underway but not yet standardized, and private cloud and public cloud remain disconnected.

This role exists to join the dots, establish unified ownership, and ensure that cloud strategy is not just designed-but delivered. The team needs a leader who can push architectural thinking in the right direction, remove blockers, and execute at scale.

Required Experience & Profile

• 12+ years in cloud, private cloud, infrastructure, or platform engineering
• 5+ years leading managers and senior technical leaders
• Demonstrated experience across both private and public cloud (core requirement)
• Deep private cloud expertise plus strong public cloud experience across at least two of:
  • AWS
  • GCP
  • Azure
• Strong Infrastructure‑as‑Code background (Terraform, Ansible, Python, or equivalent)
• Proven experience building self‑service internal platforms or IaaS products
• Strong foundation in networking, security, identity, and distributed systems
• Track record of earning trust and leading large, senior engineering organisations
• Known as an executor – able to drive strategy into delivery

Nice to Have

• Leadership experience with OpenShift or upstream Kubernetes
• Experience delivering portal‑ or GUI‑based private cloud platforms
• Background in DevOps, SRE, or Internal Developer Platforms (IDPs)
• Exposure to AI/ML or GPU‑driven workloads

Ideal Background

This role is best suited to candidates from stable, established technology organisations, particularly environments where private cloud and public cloud have coexisted over time. Familiarity with enterprises that use “private cloud” or “hybrid/cloud platform” terminology and architectures will be beneficial. Strong open‑source fluency and comfort operating in large, complex engineering environments are key to success.

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Lead Computer Vision Engineer – Multimodal AI Systems
Location: New York City or Remote (US-based)
Up to $300k base

Our client is a fast-scaling AI startup tackling complex real-world challenges with cutting-edge technology. They are building intelligent systems that combine computer vision, multimodal models, and generative AI to transform how industries operate. With strong venture backing and enterprise clients already onboard, this is a chance to join a high-growth environment where your work will directly impact mission-critical workflows.

We are seeking a Lead Computer Vision Engineer with a proven track record in both technical excellence and team leadership. This role is ideal for someone who can bridge hands-on engineering with mentoring and managing a team, helping to set technical direction while ensuring delivery of production-ready AI systems. You’ll play a pivotal role in building advanced vision pipelines (detection, segmentation, transformers, 3D vision) and integrating them with large language models (LLMs) and vision-language models (VLMs) into real-world multimodal systems.

Responsibilities:

• Lead and mentor a team of computer vision and ML engineers, fostering collaboration and growth

• Define and drive the technical roadmap for vision-related projects

• Architect and deliver computer vision solutions across detection, segmentation, classification, 3D perception, and multimodal workflows

• Oversee integration of CV models with LLMs/VLMs for reasoning and automation

• Collaborate with cross-functional teams to bring research to scalable production systems

• Stay up to date on cutting-edge research (transformers, diffusion, multimodal agents) and apply relevant innovations

Requirements:

• 6+ years of professional experience in computer vision, deep learning, or applied ML

• Minimum 2+ years in a management role with proven team or project leadership

• Hands-on expertise with frameworks such as PyTorch or TensorFlow

• Solid track record deploying production-ready CV systems at scale

• Experience with vision transformers, multimodal models (CLIP, BLIP, Flamingo, etc.), and generative AI

• Strong communication skills, able to work with both technical and non-technical stakeholders

• US-based (NYC preferred, remote possible)

Nice to Have:

• Background in robotics, industrial AI, or applied CV in real-world environments

• Contributions to open-source CV/AI projects or publications in top-tier conferences

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