Lead full stack software engineering for customer‑facing SaaS products, owning design, implementation, and operational readiness across frontend and backend.
Locations (2)
Bangalore, Karnataka, India
India
Responsibilities
Design, build, and evolve scalable full stack product features and customer‑facing cloud applications.
Own complex product capabilities end‑to‑end, from detailed technical design through frontend and backend implementation to production readiness.
Remain deeply hands‑on, writing high‑quality code and solving complex technical problems across the stack.
Partner with Architects, Product and UX to translate customer needs and product direction into production software.
Improve the reliability, performance, security, observability, testability and maintainability of our applications and services.
Lead gameplay programming for AI systems in Cyberpunk 2, designing and implementing low-level systems for open world AI and procedural content.
Compensation
Estimated pay range for this position: $180,100 - $247,600 CAD annually. This role may be eligible for a long term incentive program (option to purchase CDPR stock after the vesting period).
Responsibilities
Work closely with designers and other developers to understand their needs and ensure efficient world population
Build and maintain major systems for open world spawning, AI, and systemic gameplay
Monitor performance and memory usage, optimizing as needed
Oversee technical efforts of other developers through code reviews and mentoring
Develop debug and designer tools for non-deterministic gameplay
Building and maintaining high-performance infrastructure for large-scale LLM training, reinforcement learning, and inference, including distributed runtimes and GPU cluster scheduling.
Locations (2)
New York City, New York, United States
Paris, Île-de-France, France
Responsibilities
Design, build, and operate distributed training and inference infrastructure for large language models, including Mixture-of-Experts models
Scale training with parallelism strategies (data, tensor, pipeline, and expert), memory optimization, checkpointing, and failure recovery
Build inference and rollout systems that support evaluation, experimentation, and RL without slowing down training
Build execution environments and sandboxes for online RL and agent post-training
Own continuous performance validation: regular benchmarks of rollout speed, training throughput, and learning behavior
Lead LLM inference optimization for Qualcomm Cloud AI accelerators, working with customers and internal teams to deploy and tune generative AI workloads.
Responsibilities
Deploy and optimize LLM and multimodal inference workloads on Qualcomm Cloud AI accelerator platforms
Profile and optimize prefill and decode performance metrics
Analyze model architecture and runtime bottlenecks across compute, accelerator memory, host memory, KV cache, interconnect, networking, and software stack
Optimize model execution using quantization, batching, continuous/dynamic batching, KV-cache management, paged attention, prompt/context-length tuning, and speculative decoding
Optimize distributed inference across tensor, pipeline, data, context, and expert parallelism
Requirements
Master’s degree or higher in Computer Science, Electrical/Computer Engineering, AI/ML, or related technical field
Lead the design, development, and maintenance of Unity’s AI asset creation APIs and SDKs, ensuring secure, reliable, and observable backend services while collaborating with partners and internal teams to advance generative AI capabilities for game developers.
Compensation
Base Salary Range: We determine the base salary range for this role based on your primary work location:
Zone A: $157,800 - $236,800 USD gross
Zone B: $178,300 - $267,500 USD gross
Zone C: $200,400 - $300,600 USD gross
Responsibilities
Own the shared API and SDK layer consumed by Unity products
Ensure backend services are secure, reliable, and observable
Develop and maintain new integrations with partners
Set patterns and practices for AI-assisted development
Support and improve CI, release, and incident management processes
Company-paid medical healthcare (dental, vision, and mental).
Free mental health support, including access to counseling, psychiatric care, and a variety of well-being webinars.
Paid leave — 26 days of vacation, 10 sick days, & 12 calendar holidays per year.
RRSP with employer matching.
Lifestyle Spending Account (LSA) – $100 per month to use towards fitness, wellness, internet, home office equipment, learning, streaming services, and more.
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