{"id":68128,"url":"https://alion.io/job/daloopa-senior-backend-engineer-ml-llm","title":"Senior Backend Engineer - ML / LLM","company":{"id":9231,"name":"Daloopa","domain":"daloopa.com","url":"https://alion.io/company/daloopa","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":25000,"max_usd":55000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":29},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Celery","optional":false},{"name":"Django","optional":false},{"name":"DynamoDB","optional":false},{"name":"FastAPI","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false}],"status":"closed","first_seen_at":"2026-08-21T00:32:03Z","employer_posted_date":null,"last_verified_at":"2026-10-20T00:32:08Z","board_verified":false,"closed_at":"2026-10-20T00:32:08Z","days_open":60,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":60},"description":"As a Senior Backend Engineer on the ML side, you'll build the platform that makes this loop work: the systems that turn analyst corrections into structured training signals, the pipelines that move PDFs and HTML filings into model-ready data, the route extraction work to humans when models are uncertain, and the feed of the results back into the next training cycle. If you're excited by AI systems where humans and models actually collaborate, this is the role.\nResponsibilities:\nBuild and scale the supervised learning platform that turns analyst corrections into training data, the connective tissue between our human-in-the-loop process and our models.\nDesign and operate extraction pipelines that turn PDFs and HTML filings into structured, audit-ready data, in partnership with the ML team.\nBuild routing and uncertainty-aware systems that decide when a model can act alone and when an analyst needs to weigh in.\nIntegrate LLMs and ML models into production via API endpoints and inference pipelines, with the reliability and observability clients require.\nDefine database schemas and architectural decisions for performance, scalability, and resilience across a domain that spans every public market and accounting convention.\nChampion clean, maintainable code through reviews, tests, and clear documentation.\nRequirements:\n4+ years of professional backend engineering experience.\nStrong expertise in Python and Django (or equivalent backend frameworks).\nHands-on experience integrating ML models or LLMs into production, including model serving, inference APIs, and vector stores.\nDeep understanding of relational and non-relational databases (PostgreSQL, MySQL, Redis, DynamoDB).\nExperience with distributed systems, caching, and asynchronous task queues (Celery or equivalent).\nTrack record of leading backend or ML-integrated projects end-to-end.\nGenuine interest in the problem domain of financial data, supervised learning systems, or human-in-the-loop AI.\nBonus Points for:\nExperience building human-in-the-loop or active learning systems where labeled data quality directly determines model performance.\nExperience extracting structured data from messy real-world documents (PDFs, HTML, scanned content at scale).\nBackground in fintech, financial data, or other domains where data quality is mission-critical and audit trails matter.\nFamiliarity with the financial fundamentals landscape, including 10-Ks, 10-Qs, transcripts, segment reporting, and non-GAAP reconciliations.\nPrior experience at growth-stage startups where you've scaled systems through major growth phases.","description_format":"text","description_chars":2590,"description_truncated":false,"requirements":{"experience_years_min":4,"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":["Artificial Intelligence","Financial AI","Document AI","Financial Data & Market 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