{"id":3347972,"url":"https://alion.io/job/intellectsoft-machine-learning-engineer-researcher-ir-556","title":"Machine Learning Engineer / Researcher (IR-556)","company":{"id":5207,"name":"Intellectsoft","domain":"intellectsoft.com","url":"https://alion.io/company/intellectsoft","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India","Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":".NET","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"PEFT","optional":false},{"name":"Pre-training","optional":false},{"name":"QLoRA","optional":false},{"name":"SFT","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Transformers","optional":false},{"name":"Accelerate","optional":true},{"name":"C#","optional":true},{"name":"DeepSpeed","optional":true},{"name":"DPO","optional":true},{"name":"FSDP","optional":true},{"name":"GRPO","optional":true},{"name":"Hugging Face","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"llama.cpp","optional":true},{"name":"Model Distillation","optional":true},{"name":"Ollama","optional":true},{"name":"Perplexity","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Quantization","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"Reward Modeling","optional":true},{"name":"RLHF","optional":true},{"name":"SQL","optional":true},{"name":"TensorRT","optional":true},{"name":"TensorRT-LLM","optional":true},{"name":"TGI","optional":true},{"name":"Tokenization","optional":true},{"name":"TRL","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-10-27T17:47:11Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-28T08:05:34Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Intellectsoft is a software development company delivering innovative solutions since 2007. We operate across North America, Latin America, the Nordic region, the UK, and Europe. We specialize in industries like Fintech, Healthcare, EdTech, Construction, Hospitality, and more, partnering with startups, mid-sized businesses, and Fortune 500 companies to drive innovation and scalability. Our clients include Jaguar Motors, Universal Pictures, Harley-Davidson, and many more where our teams are making daily impactTogether, our team delivers solutions that make a difference. Learn more at www.intellectsoft.net\nOur client is a management consulting and technology firm focused on transforming global healthcare and diverse industries through data-driven strategies, cutting-edge analytics, and advanced AI solutions. This role sits within a focused research initiative dedicated to adapting small language models (SLMs) to specialized, high-value domain applications.\nRequirements\nExperience: 3+ years in Machine Learning Engineering or Applied ML, with hands-on experience fine-tuning transformer-based language models.\nCore Tech Stack: Advanced Python and PyTorch proficiency.\nFrameworks & Ecosystem: Deep fluency in the Hugging Face ecosystem, including Transformers, PEFT, Datasets, Accelerate, and TRL.\nFine-Tuning Expertise: Practical command of SFT with LoRA/QLoRA, alongside the judgment to reason about CPT and RL/preference methods.\nModel Selection: Strong understanding of base model architectures, tokenizer design, pre-training data distributions, licensing, and context window requirements.\nData Engineering for ML: Proven experience building training pipelines (curation, cleaning, synthetic data generation, and formatting).\nEvaluation & Serving: Ability to design executable correctness evaluations, paired with hands-on experience serving and quantizing models using at least one modern inference framework.\nResearch Fluency: Comfort reading recent ML research papers and translating state-of-the-art methods into working code.\nNice to have\nHands-on experience with Continued Pre-Training (CPT) on large domain corpora.\nExperience with Reinforcement Learning / preference optimization for LLMs (reward modeling, DPO, GRPO, or verifiable-reward setups).\nExperience with structured-output generation, code generation (e.g., SQL/DDL), or domain classification fine-tuning.\nFamiliarity with distributed training frameworks (DeepSpeed, FSDP).\nKnowledge distillation experience transferring capabilities from large teacher models to small student models.\nExperience with on-device or edge deployment.\nActive open-source contributions to machine learning tooling, libraries, or published models.\nResponsibilities\nOwn the Model Adaptation Lifecycle: Drive end-to-end adaptation of SLMs to specialized domain tasks, choosing the right base models, training strategies, and architectures.\nApply Efficient Fine-Tuning: Implement parameter-efficient fine-tuning (PEFT) methods with a mathematically grounded understanding of low-rank adaptation (LoRA, QLoRA, rank selection, parameterization, scaling, and accuracy-efficiency trade-offs).\nSelect Strategy per Task: Determine and sequence optimal adaptation strategies - including Continued Pre-Training (CPT), Supervised Fine-Tuning (SFT), and RL/preference tuning (DPO, GRPO, RLHF).\nCurate & Synthesize Data: Clean, curate, format, and generate high-quality datasets, including synthetic data generation when domain data is scarce.\nDesign Functional Evaluations: Build task-specific benchmarks grounded in functional, executable correctness rather than loss curves or perplexity alone, maintaining regression tracking across versions.\nLeverage Knowledge Transfer: Use larger models as teachers to transfer capabilities to SLMs via distillation, structured pruning, and quantization.\nDeploy & Optimize Serving: Stand up and optimize inference infrastructure across GPU, CPU, and edge targets using frameworks such as vLLM, TGI, Ollama, llama.cpp, or TensorRT-LLM.\nPipeline Reproducibility & Research Execution: Break target tasks into milestones with clear criteria, maintaining reproducible pipelines with data/config versioning, checkpointing, and experiment tracking.\nTranslate recent literature into reproducible experiments.\nBenefits\nEmployment-based cooperation\nComprehensive insurance for you and your family (health, life, and accident)\nPaid PTO policy (vacation, sick leaves, and public holidays)\nTech equipment provided\nUdemy courses, workshops, trainings & expert knowledge-sharing\nFlexible hours & work setup","description_format":"text","description_chars":4577,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Mobile App Development Services","Web Development Services","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-10-27T17:47:11Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":35,"reasons":["conf:2","win:early"],"computed_at":"2026-10-28T05:59:10Z"},"pay":null,"html_url":"https://alion.io/job/intellectsoft-machine-learning-engineer-researcher-ir-556","json_url":"https://alion.io/job/intellectsoft-machine-learning-engineer-researcher-ir-556.json","meta":{"generated_at":"2026-10-28T08:56:54Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":11589,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-29T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":5207},"rest":"https://alion.io/mcp/rest/get_company?id=5207"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fintellectsoft-machine-learning-engineer-researcher-ir-556"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fintellectsoft-machine-learning-engineer-researcher-ir-556"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fintellectsoft-machine-learning-engineer-researcher-ir-556"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/intellectsoft-machine-learning-engineer-researcher-ir-556\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fintellectsoft-machine-learning-engineer-researcher-ir-556"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3347972}},{"tool":"search_jobs","arguments":{"company":"intellectsoft.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3347972},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. Docs: https://alion.io/developers"}}