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Machine Learning (ML)We are looking for a Senior Backend Engineer to build and operate the core AI/ML-backed systems that power large-scale, consumer-facing products. You will work on production-grade AI runtimes, retrieval systems, and ML-adjacent backend infrastructure, making pragmatic tradeoffs across quality, latency, reliability, and cost.
This role is not an entry point into AI/ML. You are expected to already have hands-on experience shipping ML-backed backend systems in production.
At Proximity, you won’t just build APIs - you’ll own critical backend systems end-to-end, collaborate closely with Applied ML and Product teams, and help define the foundations that power intelligent experiences at scale.
Responsibilities -
- Own and deliver end-to-end backend systems for AI product runtime, including orchestration, request lifecycle management, state/session handling, and policy enforcement.
- Design and implement retrieval and memory primitives end-to-end — document ingestion, chunking strategies, embeddings generation, indexing, vector/hybrid search, re-ranking, caching, freshness, and deletion semantics.
- Productionize ML workflows and interfaces, including feature and metadata services, online/offline parity, model integration contracts, and evaluation instrumentation.
- Drive performance, reliability, and cost optimization, owning P50/P95 latency, throughput, cache hit rates, token and inference costs, and infrastructure efficiency.
- Build observability by default, including structured logs, metrics, distributed tracing, guardrail signals, failure taxonomies, and reliable fallback paths.
- Collaborate closely with Applied ML teams on model routing, prompt and tool schemas, evaluation datasets, and release safety gates.
- Write clean, testable, and maintainable backend code, contributing to design reviews, code reviews, and operational best practices.
- Take systems from design → build → deploy → operate, including on-call ownership and incident response.
- Continuously identify bottlenecks and failure modes in AI-backed systems and proactively improve system robustness.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 6–10 years of experience building backend systems in production, with 2–3+ years working on ML/AI-backed products such as search, recommendations, ranking, RAG pipelines, or AI assistants.
- Strong practical understanding of ML system fundamentals, including embeddings, vector similarity, reranking, retrieval quality, and evaluation metrics (precision/recall, nDCG, MRR).
- Proven experience implementing or operating RAG pipelines, covering ingestion, chunking, indexing, query understanding, hybrid retrieval, and rerankers.
- Solid distributed systems fundamentals, including API design, idempotency, concurrency, retries, circuit breakers, rate limiting, and multi-tenant reliability.
- Experience with common ML/AI platform components, such as feature stores, metadata systems, streaming or batch pipelines, offline evaluation jobs, and A/B measurement hooks.
- Strong proficiency in backend programming languages and frameworks (e.g., Go, Java, Python, or similar) and API development.
- Ability to work independently, take ownership of complex systems, and collaborate effectively with cross-functional teams.
- Strong problem-solving, communication, and system-design skills.
Desired Skills -
- Experience with agentic runtimes, including tool-calling or function-calling patterns, structured outputs, and production guardrails.
- Hands-on exposure to vector and hybrid retrieval stacks such as FAISS, Milvus, Pinecone, or Elasticsearch.
- Experience running systems on Kubernetes, with strong knowledge of observability stacks like OpenTelemetry, Prometheus, Grafana, and distributed tracing.
- Familiarity with privacy, security, and data governance considerations for user and model data.
Benefits
- Best in class compensation: We hire only the best, and we pay accordingly.
- Proximity Talks: Meet engineers, designers, and product leaders — and learn from experts across domains.
Keep on learning with a world-class team: Work on real, production AI systems at scale, challenge yourself daily, and grow alongside some of the best minds in the industry.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Proximity Works
About
We are Proximity - a global team of coders, designers, product managers, geeks and experts. We solve hard, long-term engineering problems and build cutting edge tech products.
About us
Born in 2019, Proximity Works is a global, fully distributed tech firm headquartered in San Francisco - with hubs across Mumbai, Dubai, Toronto, Stockholm, and Bengaluru. We’re in the business of solving high-stakes engineering challenges with AI-powered solutions tailored for industries like sports, media & entertainment, fintech, and enterprise platforms. From real-time game analytics and ticketing workflows to creative content generation, we help build software that serves millions every day.
About the Founders
At the helm is Hardik Jagda, CEO - a technologist with a startup DNA who brings clarity to complexity and a passion for building delightful experiences.
Milestones & Impact
- Trusted by some of the world’s biggest players - from major media & entertainment giants to one of the world’s largest cricket websites and the second-largest stock exchange in the world.
- Delivered game-changing tech: slashing content creation by 90%, doubling performance metrics for NASDAQ clients, and accelerating speed/performance wins for platforms like Dream11.
Culture & Why It Matters
- Fully distributed and flexible: work 100% remotely, design your own schedule, build habits that work for you and not the other way around.
- People-first culture: Community events, “Proxonaut battles,” monthly off-sites, and a liberal referral policy keep us connected even when we’re apart.
- High-trust environment: autonomy is encouraged. You’re empowered to act, learn fast, and iterate boldly. We know great work comes when talented people have space to think and create.
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Follow CutshortShubham Vishwakarma
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