{"id":2769171,"url":"https://alion.io/job/secninjaz-technologies-llp-aiml-engineer-data-evaluation-model-improvement","title":"AI/ML Engineer Data, Evaluation & Model Improvement","company":{"id":4442839,"name":"SecNinjaz Technologies LLP","domain":"secninjaz.com","url":"https://alion.io/company/secninjaz-technologies-llp","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":"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":["Delhi, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":12500,"max_usd":32000,"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":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"AI Agents","optional":true},{"name":"DPO","optional":true},{"name":"Embeddings","optional":true},{"name":"Function Calling","optional":true},{"name":"Git","optional":true},{"name":"Hugging Face","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"Linux","optional":true},{"name":"LoRA","optional":true},{"name":"Machine Learning","optional":true},{"name":"Model Distillation","optional":true},{"name":"PEFT","optional":true},{"name":"Post-training","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"QLoRA","optional":true},{"name":"RAG","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"SFT","optional":true},{"name":"Structured Outputs","optional":true},{"name":"Tool Use","optional":true},{"name":"Transformers","optional":true},{"name":"TRL","optional":true}],"status":"live","first_seen_at":"2026-10-10T18:58:26Z","employer_posted_date":null,"last_verified_at":"2026-10-10T18:58:26Z","board_verified":false,"closed_at":null,"days_open":6,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":6},"description":"AI/ML Engineer — Data, Evaluation & Model Improvement\nFocus: LLM evaluation, fine-tuning and continuous product improvement\nCompany: SecNinjaz Technologies LLP\nExperience: Around 2 years of relevant hands-on experience\nEmployment: Full-time, on-site\nLocations: Netaji Subhash Place, New Delhi, \nAbout the opportunity\nAt SecNinjaz, we are building an AI-powered Vulnerability Assessment and Penetration Testing (VAPT) product that helps organisations identify, investigate and validate security weaknesses in authorised environments.\nWe are looking for an AI/ML Engineer who can build trustworthy datasets, evaluate model and agent performance, and turn measured weaknesses into practical improvements through better data, retrieval and fine-tuning.\nYou will own the engineering work that helps us answer three questions: Where does the system fail What should we improve Does the change perform better on unseen cases\nStrong applied AI/ML skills are essential. Cybersecurity or VAPT experience is a plus. Our security specialists will help define domain labels, review evidence and validate security findings.\n\nWhat you will work on\nData pipelines: Transform approved agent traces, tool outputs, expert feedback and verified outcomes into structured, versioned datasets.\nData quality: Implement cleaning, deduplication, annotation workflows, provenance tracking and sensitive-data handling.\nEvaluation datasets: Create training, validation and held-out test sets, preventing related cases or near-duplicate examples from leaking across splits.\nModel and agent evaluation: Build repeatable evaluations for task completion, tool-use accuracy, evidence quality, false positives, latency and compute cost.\nFailure analysis: Investigate whether failures originate from the model, prompts, retrieval, tools, data or workflow design, and recommend the appropriate improvement.\nFine-tuning: Run reproducible supervised fine-tuning experiments, including approaches such as LoRA or QLoRA where suitable.\nRetrieval improvement: Evaluate embeddings, rerankers and retrieval pipelines to improve the relevance of the information supplied to agents.\nExperiment tracking: Record dataset versions, configurations, model checkpoints, metrics and failure cases so another engineer can reproduce the results.\nProduct integration: Work with the runtime engineer to integrate accepted models and improvements with compatibility tests, regression checks and rollback support.\nFeedback pipelines: Turn reviewed product failures into candidate dataset, evaluation or model improvements before promoting them into a release.\nWhat we are looking for\nStrong Python skills and practical experience building data processing or machine learning pipelines.\nWorking knowledge of PyTorch and the Hugging Face ecosystem, or comparable tools.\nA hands-on LLM fine-tuning or post-training project covering data preparation, a baseline, held-out evaluation and failure analysis.\nUnderstanding of training versus inference, overfitting, generalisation, loss functions and evaluation metrics.\nFamiliarity with dataset quality, annotation, deduplication and data leakage prevention.\nUnderstanding of LLM prompting, structured outputs, retrieval and tool use.\nAbility to work with Linux, Git, GPU environments and reproducible experiment configurations.\nAbility to explain why a change improved results—or why it should be rejected.\nA well-executed research project, substantial personal project or implemented coursework can demonstrate relevant skills. Be ready to explain your contribution and the limitations of your results.\nGood to have\nFamiliarity with cybersecurity, VAPT workflows, vulnerability reports or security datasets.\nExperience with preference optimisation, DPO, reinforcement learning or distillation.\nExposure to PEFT, TRL, experiment tracking and dataset versioning tools.\nExperience with model quantisation, GPU memory optimisation or distributed training.\nExperience evaluating RAG systems, embeddings, rerankers or agent trajectories.\nFamiliarity with private model deployment and inference serving.\nYou do not need experience with every technology listed.\nWhat you will gain\nHands-on access to SecNinjaz's on-premises NVIDIA H200 GPU infrastructure for planned product training, fine-tuning, evaluation and inference workloads.\nAn opportunity to deepen your expertise through real experiments and measurable product outcomes.\nCollaboration with cybersecurity specialists who can help turn domain expertise into high-quality datasets and evaluations.\nOwnership of the improvement process, from identifying a failure to evaluating and integrating a better solution.\nYour initial contribution\nEstablish a reviewed dataset and evaluation baseline, then run a bounded model-improvement experiment. Compare the candidate against the baseline on unseen cases and make an evidence-based recommendation on adoption.\nHow to apply\nApply through LinkedIn with your CV and a relevant project link, \nWe are especially interested in how you measured improvement, prevented data leakage and investigated failures.\n\nOr \nemail your CV to [HIDDEN TEXT] with a short technical write-up explaining your dataset, fine-tuning approach, evaluation results and personal contribution.and completed and ongoing AI/agentic AI projects, your specific contributions, current CTC, expected CTC, and notice period or earliest date you can join SecNinjaz.","description_format":"text","description_chars":5406,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Information Security"],"lifecycle":[{"event":"open","at":"2026-10-17T03:17:59Z"}],"visa":[],"liveness":{"score":83,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.831,"p_room":1,"age_days":6,"expected_fill_days":19,"reasons":["seen:6","win:early","comp:junior"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/secninjaz-technologies-llp-aiml-engineer-data-evaluation-model-improvement","json_url":"https://alion.io/job/secninjaz-technologies-llp-aiml-engineer-data-evaluation-model-improvement.json","meta":{"generated_at":"2026-10-17T16:28:54Z","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":22651,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"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":4442839},"rest":"https://alion.io/mcp/rest/get_company?id=4442839"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsecninjaz-technologies-llp-aiml-engineer-data-evaluation-model-improvement"},{"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%2Fsecninjaz-technologies-llp-aiml-engineer-data-evaluation-model-improvement"},{"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%2Fsecninjaz-technologies-llp-aiml-engineer-data-evaluation-model-improvement"},{"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/secninjaz-technologies-llp-aiml-engineer-data-evaluation-model-improvement\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsecninjaz-technologies-llp-aiml-engineer-data-evaluation-model-improvement"}]}