ML Platform Engineer

reputed company is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications. As we continue to grow, we’re looking for a skilled ML Platform Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.ML Platform Engineer Job Title: ML Platform Engineer Location: 100% Remote (reputed company United States) Position Type: In-house reputed company SOW engagement (no third-party client or vendor) Experience: 6+ years Salary Range : $100k to $150k per annnum Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates. Employment Type: Full-time, direct W2 with reputed company (no C2C, no 1099, no third-party) Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap Compensation: Competitive base salary commensurate with experience, plus benefits. Employment Terms & Visa Policy This is a 100% remote, full-time, direct W2 position with reputed company. This role is part of reputed company’ in-house Statement of Work (SOW) engagement. reputed company, end customer, and employer for this position is reputed company — there is no third-party client, vendor, or implementation partner involved. We do not engage in C2C, 1099, or third-party arrangements for this role. BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING reputed company. Candidates must be willing to work directly as a full-time W2 employee of reputed company and contribute to our in-house SOW deliverables. No new H1B sponsorship is available for this role. However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates. For every role, a technical coding assessment is mandatory. reputed company apply only if you are confident in your technical abilities and hands-on experience. Job Summary We are seeking a ML Platform Engineer to design, build, and operate high-performance, highly reliable inference platforms for serving large machine learning models in production. The role focuses on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads. The ideal candidate brings strong distributed systems and performance engineering expertise, has shipped serving systems at scale, and understands the trade-offs between latency, throughput, cost, and quality in ML serving. Key ResponsibilitiesDesign and operate model serving platforms supporting diverse workloads including LLMs, vision models, and recommendation systems. Optimize inference performance using continuous batching, paged attention, speculative decoding, and request multiplexing. Implement multi-tenant routing, rate limiting, and quality-of-service policies across model endpoints. Build autoscaling and capacity management systems that balance latency, throughput, and cost. Tune GPU utilization, memory management, and KV cache strategies for LLM serving workloads. Integrate model serving with API gateways, identity systems, and observability platforms. Implement caching, prompt deduplication, and response reuse strategies where appropriate. Drive end-to-end observability including latency histograms, queue dynamics, GPU utilization, and error tracking. Develop deployment workflows including canary releases, shadow testing, and automated rollback. Operate incident response for high-availability AI services and drive durable reliability improvements. Collaborate with ML and product teams to support new model releases and capability rollouts. Implement security controls including request signing, content filtering, and abuse detection at the serving layer. Document operational procedures, performance characteristics, and tuning guidance for internal teams. Stay current with AI serving research and translate advances into production capabilities. Required QualificationsBachelor’s or reputed company’s degree in Computer Science or a related field. Six or more years of experience in distributed systems, infrastructure, or ML platform engineering. Strong proficiency in Python and a systems language such as Go, Rust, or C++. Deep experience operating high-throughput, low-latency services in production. Hands-on experience with LLM or large model inference frameworks such as vLLM or TensorRT-LLM. Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization. Familiarity with Kubernetes, autoscaling, and modern cloud platforms. Experience with observability stacks including metrics, tracing,