Data Scientist / ML Engineer – Surgical Intelligence

What you'll actually own

You turn raw sensor data into surgical intelligence, and that intelligence is the heart of what makes Zooly different. Our edge is telling a surgeon something they cannot get on their own, and that only exists if the data pipelines, features, models, and validation behind it are real and trustworthy. You build that across the hip, knee, and shoulder products: clean, synchronized data, honest ground truth, models that hold up, and evidence you can defend. The best of this work is creative and simple at once. If Zooly can sense what no one else can, it will be in large part because of the intelligence you built.

Where the business is 12 months after you join

If this hire goes the way we intend, one year from now:

• There are solid data pipelines and reproducible analyses that the whole company builds on.
• The models that power Zooly's differentiator are validated against honest ground truth, with accuracy that is credible and independently measured.
• You have defined the ground truth, metrics, and failure modes that keep our algorithm claims defensible.
• You deliver predictably within the shared platform cadence, working as one team with the US.

About Zooly

Zooly Labs is on a mission to make advanced surgical guidance more accessible for joint replacement surgery. Joint replacement can restore mobility and quality of life, yet surgeons often have limited objective information during the procedure to assess joint behavior and guide decisions. We build AI-guided technology that combines intelligent sensing, real-time data, and decision support with familiar surgical workflows and standard instruments, without large capital equipment. We are an early-stage company building a scalable platform across hip, knee, and shoulder.

How we work at Zooly

Patient-driven. Design-obsessed. We're an in-person team of curious, driven people who care about getting the details right, because there's a patient on the table counting on us. A few beliefs shape how we build, and this role lives at the center of them.

• Master your craft. We invest in people who go deep. There is no ceiling that forces a great engineer or designer into management to advance. Go as far into your craft as you want.
• The patient is why. Behind every procedure is a person counting on the people who built the tools. That is what keeps our standards high and our design work honest.
• Act like an owner. We take responsibility for our decisions and how we communicate, we think long-term, and we bias toward action.

What this role is really like

This is a hands-on role at a fast-growing startup racing real deadlines. You will wrangle messy sensor data, engineer features, train and validate models, and then argue honestly about what the results really show. You care as much about leakage, drift, and ground truth as about accuracy numbers. If you want clean benchmark datasets handed to you, this is not the role. If you want to build the intelligence that makes a medical product different, it is.

What you'll do

• Build data pipelines, cleaning and synchronization tools, feature engineering, model evaluation, algorithm validation, visualization, and reproducible analyses.
• Build reusable platform modules instead of one-off, joint-specific solutions wherever you can.
• Take part in sprint planning, design and code reviews, test planning, and documentation.
• Investigate defects and failures and write up root cause and the fix.
• Keep configuration control, test evidence, and clean engineering records.
• Work closely with the product engineers, the US platform leads, and quality/regulatory contributors.

What you need to be able to do

These are capabilities, not credentials. If you can do these things, we want to talk regardless of how many years it took you to get here.

• You have applied time-series analysis, signal processing, machine learning, sensor analytics, or biomechanics-data work to real algorithm development.
• You are strong in Python with PyTorch, TensorFlow, scikit-learn, Pandas, and SQL.
• You have a solid foundation in statistics, experimental design, model evaluation, cross-validation, uncertainty, and data visualization.
• You have built end-to-end ML workflows: ingestion, cleaning and synchronization, labeling, feature engineering, training, validation, evaluation, versioning, and deployment.
• You can define meaningful ground truth and metrics and spot bias, leakage, drift, confounding, and failure modes.
• You can explain algorithm behavior, limits, and evidence to engineering, clinical, quality/regulatory, and executive audiences.
• An advanced degree (MS or PhD) in a quantitative field is common in people who do this well, and strong industry experience counts too, but the ability above matters more than the diploma.

What would make you a strong fit

• Experience with medical devices, surgical data, biomechanics, wearable sensors, robotics, digital health, or other physiologic sensor time-series.
• Experience with quaternions, rigid-body kinematics, sensor fusion, force/pressure signals, event detection, anomaly detection, or real-time inference.
• Experience deploying algorithms into production software, embedded/edge systems, or clinician-facing applications.
• Familiarity with AI/ML medical-device validation, design controls, software lifecycle documentation, and change management.
• Experience working with clinicians or surgeons to define labels, endpoints, clinically interpretable outputs, and prospective data collection.

How this role works with the rest of the team

You are part of one shared engineering team. You are based in India, but the backlog, architecture, and design reviews are global. You work closely with the US software, electronics, and product engineers across overlapping hours. Your work is central to the differentiator, so you are deeply connected to the whole company, not off to the side.

Stay curious

We hire curious people. The kind who took things apart as kids and never stopped asking how things work. If that sounds like you, we'd love to meet.

The fine print

Zooly Labs is an equal opportunity employer and evaluates candidates without regard to legally protected characteristics. Responsibilities will evolve as the company and product portfolio grow. This role is based in India and works closely with the US team across overlapping hours. Compensation, benefits, and employment details will be discussed directly.