Computer Vision Engineer

Computer Vision Engineer Do you want to work at the intersection of cutting‑edge technology and workplace safety, ensuring every employee returns home safely every day? Are you excited by the challenge of building complex machine learning solutions that detects and understands complex environments? Join Buddywise! About Buddywise

We’re building a safety intelligence platform to prevent workplace accidents before they happen. Backed by highly respected industry leaders and VCs, our AI‑powered system helps industrial and infrastructural companies detect, predict, and act on real‑world risks.

We’re a small, fast‑moving team working at the intersection of AI, computer vision, and real‑world safety. Our customers span manufacturing, logistics, chemical, and construction industries. If you thrive in a high‑pace, high‑responsibility environment and want to make workplaces safer than ever, Buddywise is the place for you.

As a part of our Engineering team, you will work on developing models and systems to solve complex Safety issues in complex Industrial environments. You will develop new models for new use cases and refine existing designs to accommodate changing behaviours. You will bring the SOTA models, techniques and guidelines to the team to keep up with the rapidly changing ML world.

• 5+ years of experience delivering software services powered by machine learning
• Experience working with cloud infrastructure such as AWS, GCP or Azure
• Fluent in Python;
• Demonstrated experience managing the technical direction of a software system
• Experience in coaching and mentoring senior engineers
• Hands‑on experience with modern ML frameworks (e.g., PyTorch)
• Proven experience delivering ML/CV models to production environments, including:
  Model compilation & optimization (e.g., Tensor
  
  RT, ONNX Runtime) for accelerated inference. Containerization using Docker for reproducible and scalable deployments
• Knowledge of MLOps concepts and tools for data labeling, experiment tracking, pipeline orchestration, CI/CD, and production monitoring. Eg:
  Label Studio, WandB, Grafana, Git Hub Actions, MLflow, Docker.
• Solid understanding of the full ML model lifecycle including feature engineering, model training & evaluation, deployment, diagnostics, and ongoing monitoring.
• Experience building scalable data pipelines for ML‑based data processing
• Experience developing and maintaining services under SLA
• Analytical mindset with a problem‑solving approach
• Passion for solving customer challenges quickly while making thoughtful architectural decisions
• Adaptability and resilience when facing new or ambiguous challenges
• Ability and willingness to work in a hybrid capacity from our Berlin office 3 days a week

• Have a strong sense of ownership and accountability. You don’t wait to be told or until things are clearly defined. You exemplify resourcefulness, and a bias for action.
• You’re driven by curiosity about how things work, and how to make them better. While you’re an expert, you’re humble and open to feedback.
• Are a clear communicator, both async and in‑person. You thrive in bringing clarity from ambiguity.
• You’re a great collaborator, working cross‑functionally, with engineers, PMs, and customers

• High ownership, high impact role in a purpose‑driven, high‑growth startup.
• Opportunity to shape the machine learning function.
• Berlin based hybrid setup with flexibility for focus work.
• A committed team environment where your growth is a priority.
• The chance to directly influence industrial safety and help employees go home safely every day.

We are:

• Obsessed with creating amazing software for our Customers that solves real pains and realises tangible value
• Positive by Default and thrive in doing hard things and solving problems
• Biased for Action and approach what we do with a sense of urgency
• Love to work as a team and Win Together
  , each contributing skill, fun and care
• Can balance Thinking Holistically whilst

Join us and be a part of reshaping industrial safety with Buddywise! 🚀

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