{"id":3249465,"url":"https://alion.io/job/neuranx-ai-aiml-engineer-python","title":"AI/ML Engineer - Python","company":{"id":4473894,"name":"NeuraNx.ai","domain":"neuranx.ai","url":"https://alion.io/company/neuranx-ai","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18000,"max_usd":44000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":32},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Hugging Face","optional":false},{"name":"KServe","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Ray Serve","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"SGLang","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"Transformers","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"WebSockets","optional":false},{"name":"AWQ","optional":true},{"name":"CI/CD","optional":true},{"name":"CUDA","optional":true},{"name":"Embeddings","optional":true},{"name":"GitHub","optional":true},{"name":"GPTQ","optional":true},{"name":"OCR","optional":true},{"name":"Ray","optional":true},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-10-25T17:17:49Z","employer_posted_date":null,"last_verified_at":"2026-10-25T17:17:49Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Company: NeuraNX.ai\n\nRole: AI/ML Engineer - Python\nLocation: Chennai, Tamil Nadu\nExperience: 3–5 Years\nWork Mode: Hybrid\nEmployment Type: Full-time\n\nRole Overview\n\nAs an AI/ML Engineer- Python, you will design, develop, deploy, and optimise AI/ML applications using Python, PyTorch, Hugging Face Transformers, and modern LLM inference frameworks. You will work on scalable inference APIs, model-serving pipelines, performance benchmarking, and production troubleshooting.\n\nKey Responsibilities\nDevelop AI and machine-learning applications using Python.\nIntegrate, deploy, and serve open-source LLMs and multimodal models.\nBuild scalable inference APIs using FastAPI, Flask, or similar frameworks.\nWork with Hugging Face Transformers, PyTorch, and model inference technologies.\nImplement streaming responses, asynchronous processing, and continuous batching.\nOptimise inference latency, throughput, GPU utilisation, and memory consumption.\nWork with model-serving frameworks such as vLLM, SGLang, NVIDIA Triton, TensorRT-LLM, KServe, or Ray Serve.\nDevelop model benchmarking, evaluation, and load-testing pipelines.\nMonitor model performance, response latency, throughput, and inference reliability.\nTroubleshoot model-loading failures, GPU out-of-memory errors, and runtime bottlenecks.\nWrite clean, modular, secure, maintainable, and well-tested Python code.\nResearch and evaluate emerging AI models, inference frameworks, and optimisation techniques.\n\nRequired Skills and Qualifications\n3–5 years of experience in Python development or AI/ML engineering.\nStrong programming skills in Python and experience building production-grade applications.\nHands-on experience with PyTorch and Hugging Face Transformers.\nPractical experience deploying or serving large language models.\nExperience with FastAPI, Flask, or similar backend frameworks.\nUnderstanding of LLM fundamentals, including:\nTokenisation, attention mechanisms, and context length\nKV cache and its impact on inference memory\nModel quantisation and memory optimisation\nContinuous batching and streaming inference\nHands-on experience with at least one inference or model-serving framework: vLLM, SGLang, NVIDIA Triton, TensorRT-LLM, KServe, or Ray Serve.\nExperience developing REST APIs, WebSockets, or Server-Sent Events (SSE).\nFamiliarity with PostgreSQL, Redis, or similar databases and caching technologies.\nStrong debugging, analytical, and problem-solving skills.\nGood communication, documentation, and collaboration skills.\n\nPreferred Skills\nExperience working with NVIDIA GPUs and CUDA.\nKnowledge of FP16, INT8, INT4, AWQ, or GPTQ quantisation techniques.\nExperience with embeddings, reranking, OCR, speech AI, or vision-language models.\nFamiliarity with model benchmarking, concurrency testing, and inference performance profiling.\nExperience developing Python SDKs, reusable AI libraries, or internal developer tools.\nFamiliarity with CI/CD, containerisation, and production deployment practices.\nContributions to open-source AI or machine-learning projects.\n\nEducation\nBachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related discipline.\nCandidates with strong practical experience, demonstrable AI projects, and relevant open-source contributions will also be considered.\n\nWhat We're Looking For\nA hands-on engineer who can turn AI models into reliable, production-ready applications.\nStrong ownership across design, implementation, debugging, and optimization.\nAbility to independently research, evaluate, and integrate open-source AI technologies.\nA performance-oriented mindset with an interest in scalable inference systems.\nA willingness to experiment, learn, and solve complex engineering challenges.\n\nNote: Application Process\nInterested candidates are requested to share their updated resume along with:\nGitHub profile or portfolio link\nDetails of relevant AI/ML or Python deployment projects\nCurrent location\nNotice period\nCurrent CTC and expected CTC\nPlease apply through LinkedIn or share your profile with our hiring team – [HIDDEN TEXT]\n\nJoin NeuraNX.ai and help build efficient, scalable, and production-ready AI 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