Machine Learning Engineer, ML Infrastructure (New Grads)

Unity Vector builds an Data platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform also supports large-scale model training, feature generation, and experimentation workflows that power production ML systems.

To support this growth, we need strong technical ownership to ensure our ML pipelines remain reliable, scalable, and architecturally sound.

The Role

We are seeking a ML engineer to evolve Unity Vector’s ML platform. This role focuses on building reliable infrastructure for serving machine learning models in production, or model training platform, and enabling safe, efficient experimentation across high-traffic online systems.

You will work closely with ML engineers, platform teams, and product stakeholders to ensure models can be deployed, scaled, monitored, and iterated on efficiently. You will play a key role in shaping how models are packaged, served, validated, monitored, and optimized in production environments.

This role requires strong systems thinking, deep experience with production ML infrastructure, and the ability to drive architectural improvements across teams.

What You’ll Do

• Contribute to large-scale ML infrastructure that serves production ML models with low latency and high reliability or trains production ML models.

• Optimize large-scale production model performance through model compilation, quantization, GPU acceleration, GPU kernel optimization, caching, or runtime tuning.

• Develop infrastructure for model deployment, canary testing, A/B experimentation, traffic splitting, rollback, and production validation.

• Improve observability of online ML systems through latency, throughput, error-rate, cost, saturation, and model-health monitoring.

• Build self-healing and autoscaling capabilities to support dynamic experiment traffic, changing model complexity, and production reliability requirements.

• Partner closely with ML engineers to support faster model iteration while maintaining production safety, scalability, and cost efficiency.

• Improve the reliability and reproducibility of model serving workflows, including model packaging, artifact validation, compatibility testing, and deployment automation.

• Lead architectural improvements that make the online ML platform more robust, user-friendly, scalable, and cost-efficient.

What We’re Looking For

• Experience building and operating ML infrastructure using technologies such as PyTorch, Triton Inference Server, Kubernetes, GKE, Ray, or similar distributed serving frameworks.

• Experience optimizing model performance using techniques such as model compilation, quantization, GPU acceleration, GPU kernel optimization, caching, or runtime tuning.

• Experience with distributed systems, Kubernetes, autoscaling, service reliability, and production observability.

• Strong programming skills in Python, with practical experience working on production ML systems and high-scale services.

• Experience with PyTorch and modern model deployment workflows, including model packaging, validation, and serving lifecycle management.

• Experience designing infrastructure for safe model rollout, canary testing, A/B experimentation, and automated rollback.

• Strong systems thinking, with the ability to reason about latency, throughput, reliability, scalability, and cost tradeoffs in online systems.

• Proven ability to lead technical direction and influence architectural decisions across teams without formal authority.

This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set.

Benefits

At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity

Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit .

Unity is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. Therefore, we provide employment opportunities without regard to age, race, color, ancestry, national origin, disability, gender, or any other protected status in accordance with applicable law. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

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