{"id":2769147,"url":"https://alion.io/job/trinka-artificial-intelligence-engineerresearch-engineer","title":"Artificial Intelligence Engineer/Research Engineer","company":{"id":1814474,"name":"Trinka","domain":"trinka.ai","url":"https://alion.io/company/trinka","size_band":"11-50","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":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":11000,"max_usd":28000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":12},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Google AI Studio","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"TensorFlow","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"CI/CD","optional":true},{"name":"LLaVA","optional":true},{"name":"LLM","optional":true},{"name":"OCR","optional":true},{"name":"OpenRouter","optional":true},{"name":"Quantization","optional":true},{"name":"TGI","optional":true}],"status":"live","first_seen_at":"2026-10-13T06:01:02Z","employer_posted_date":null,"last_verified_at":"2026-10-13T06:01:02Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"About Trinka AI\nTrinka AI (www.trinka.ai) is an AI-powered writing assistant designed for academic and technical writing. Built by experts in language and AI, Trinka goes beyond basic grammar checks to improve clarity, tone, and word choice. It corrects complex errors, follows academic style guides, and provides intelligent writing suggestions in real time. Trinka offers tools such as AI-assisted writing, a Paraphraser, AI Studio, Consistency Checks, Technical Checks, Language Quality Checks, Citation Checks, and a Proofread File feature to help users create polished, publication-ready documents. Available as a web app, browser plugin, Word add-in, and desktop app, Trinka also provides enterprise solutions with customization, privacy, and integration options.\n\nAbout the team\nWe are a bunch of passionate researchers, engineers, product managers, data scientists, and designers who came together to build a product that can revolutionize the way any research-intensive projects are done. Reducing cognitive load and helping people to convert information into knowledge, is at the core of our mission. Our engineering team is building a scalable platform that deals with tons of data, AI processing over the data, and interactions of users from across the globe. We believe research plays a key role in making the world a better place, and we want to make it easy to approach and fun to do!\n\n We are looking for a highly motivated AI / Data Science Engineer with 2–5 years of hands-on experience in building and deploying intelligent systems. The ideal candidate should have strong expertise in Large Language Models (LLMs), model serving (including vLLM), and agent-based architectures. This role involves designing scalable AI solutions, optimizing inference pipelines, and building production-grade AI systems.\n\nKey Responsibilities:\nDesign, develop, and deploy AI/ML models with a focus on Large Language Models (LLMs)\n Implement and optimize high-performance model serving solutions (e.g., vLLM, FastAPI, Triton)\n Build and maintain agent-based systems (Agentic AI, RAG pipelines, multi-agent workflows)\nDevelop scalable data pipelines for preprocessing, embedding generation, and retrieval\nWork on vector databases (FAISS, ChromaDB, etc.) for similarity search and RAG use cases\nOptimize inference latency, throughput, and cost for production deployments\nCollaborate with cross-functional teams to integrate AI solutions into products\nMonitor, debug, and improve deployed AI systems for reliability and performance\nStay updated with the latest advancements in LLMs, multimodal AI, and agent frameworks\n\nRequired Skills & Qualifications\n\nMinimum 1 year of hands-on experience working with Agentic AI systems (multi-agent workflows, autonomous agents, or orchestration frameworks)\n2–5 years of experience in AI / Data Science / Machine Learning\nStrong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face)\nHands-on experience with Large Language Models (LLMs) and prompt engineering\nExperience with vLLM or similar high-performance inference engines\nPractical knowledge of building agent-based systems (LangChain, CrewAI, custom agents, etc.)\nExperience with Retrieval-Augmented Generation (RAG) architectures\nFamiliarity with vector databases (FAISS, ChromaDB, Pinecone, etc.)\nStrong understanding of REST APIs and backend frameworks (FastAPI preferred)\nExperience with Docker, Kubernetes, or cloud deployments (AWS/GCP/Azure)\nSolid understanding of data structures, algorithms, and system design\n\nPreferred / Good-to-Have Skills\n\nExperience with multimodal models (LLaVA, image-to-text, OCR pipelines, etc.)\nKnowledge of 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