Adaptive ML

Engineer

• Build and maintain fast and robust GPU code, focusing on delivering performance improvements in real world applications;
• Write high-quality software in CUDA, CUTLASS, or Triton with a focus on performance and robustness;
• Profile dedicated GPU kernels, optimizing across latency/compute-bound regimes for complex workloads;
• Contribute to our product roadmap, by identifying promising trends that can improve performance;
• Report clearly on your work to a distributed collaborative team, with a bias for asynchronous written communication.

GPU Performance Engineer

Backend Engineer

• Build the foundational technology powering Adaptive ML, with a relentless focus on high-performance software engineering;
• Write production-grade Rust, combining correctness, performance, and robustness across large-scale distributed systems;
• Identify and resolve complex bugs at the intersection of software and hardware correctness in distributed environments;
• Contribute to the product roadmap by identifying promising trends and surfacing high-impact technical findings;
• Engage with research developments in generative AI and reinforcement learning to inform engineering decisions;
• Report clearly on your work to a distributed, collaborative team with a strong bias for asynchronous written communication;
• Partner with teammates across engineering, research, and product to deliver robust, scalable solutions.

Performance Engineer, Rust

Software Engineer

• Build the foundational technology powering Adaptive, with a focus on high-performance software engineering and large-scale RL research;
• Contribute to our product roadmap, by identifying promising trends and high-impact findings;
• Report clearly on your work to a distributed collaborative team, with a bias for asynchronous written communication;
• Write high-quality software in Rust, with a focus on performance and robustness;
• Profile dedicated GPU kernels in CUDA or Triton, optimizing across latency/compute-bound regimes for complex workloads;
• Identify and resolve bugs in large distributed systems, at the intersection of software and hardware correctness;
• Conduct research on large language models or diffusion models, systematically exploring how reinforcement learning can be used to personalize models;
• Own a research agenda, with a bias for at-scale, systematic empirical research.

Member of Technical Staff

• Contribute to the foundational technology powering Adaptive ML, with support and guidance from the team
• Help advance projects by implementing features, running experiments, or improving reliability
• Communicate clearly about your work and learn to collaborate in a distributed team environment
• Write clear, well-structured code (primarily in Python; exposure to systems programming is a plus, not a requirement)
• Help debug issues in distributed or ML-heavy systems
• Learn best practices for performance, testing, and robustness
• Assist with research on large language models and reinforcement learning
• Reproduce and analyze results from recent ML literature
• Support empirical experiments and help document findings
• Interns are encouraged to explore both areas of engineering and research

Member of Technical Staff, Intern

Technical Customer Success

• Lead customer-facing workload planning — understanding model usage patterns, expected throughput, and infrastructure constraints to scope solutions accurately from day one.
• Own solution architecture in the sales cycle: infra selection, TCO calculation, and performance benchmarking tailored to each prospect’s environment and LLM workloads.
• Design and deliver compelling technical demos and proof-of-concept implementations that map Adaptive ML’s capabilities directly to customer pain points and existing infrastructure.
• Respond to technical evaluations, RFPs, and security reviews; go deep with engineering and data science counterparts on architecture decisions and integration requirements.
• Partner with Account Executives to shape deal strategy, accelerate procurement timelines, and remove technical blockers standing between a prospect and a signed contract.
• Own technical onboarding end-to-end — designing integration architectures, working directly with customer engineering teams, and driving time-to-first-value.
• Support and continuously optimise live deployments: cost optimisation, performance tuning, and workload expansion across multi-geo and multi-team customer environments.
• Be the escalation point for production issues — investigating and debugging problems spanning k8s deployments, Helm configurations, model serving infrastructure, and distributed systems.
• Drive workload expansion proactively: surface new use cases, additional model workflows, and untapped product capabilities that create value across your account portfolio.
• Conduct regular technical and business reviews with customer stakeholders, translating infrastructure metrics into business impact and building the case for renewal and growth.
• Build reusable technical assets — reference architectures, integration guides, runbooks, and demo environments — that scale knowledge and accelerate future deals.
• Act as the voice of the customer internally: channel field insights directly to Product and Engineering to shape the roadmap and prioritisation.
• Contribute to infra sizing and workload planning discussions alongside Solutions and DevOps colleagues, with particular focus on the NA region (NYC/Toronto coverage).

Customer Success Engineer

DevOps Engineer

• Build systematic K8s workflows to deploy our product, either client-side on a variety of infrastructures, or internally for our cloud platform;
• you'll work closely with sales and customer success to assist product deployment, pre and post sales (POC, demos, production), both on-prem, in cloud and in our SaaS.
• you'll be part of our first line of support for customer escalation, including bugs, security escalations, special events support (scale-outs, large workshops, load tests)
• Contribute to deployment support, in particular on North America time zones. This involves both personally joining customer calls to assist onboarding and troubleshooting, but also leading and contributing to our support mechanisms such as ticket triaging and oncall process.
• Contribute to our product roadmap, by coordinating between the needs of the Commercial Staff and latest developments from our Technical Staff;
• Report clearly on your work to a distributed collaborative team, with a bias for asynchronous written communication.

Deployment DevOps Engineer

AI Engineer

• Embed directly with our customers, helping them maximize the value of their Adaptive Engine deployment;
• Experiment with pipelines to personalize models at scale, leveraging synthetic data and production feedback;
• Ensure customer success, owning problems end-to-end from ideation to deployment, validation, and production;
• Work closely with our research staff, productionizing the latest frontier research initiatives;
• Contribute to our product roadmap, identifying promising trends and customer needs;
• Report clearly on your work to a distributed collaborative team, with a bias for asynchronous written communication.