{"id":694600,"url":"https://alion.io/job/spector-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":684899,"name":"Spector","domain":"spector.ai","url":"https://alion.io/company/spector-3","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":5,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-30T05:48:23Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":53000,"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":"AI Agents","optional":false},{"name":"Machine Learning","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2025-12-13T09:15:43Z","employer_posted_date":"2025-12-13","last_verified_at":"2026-10-30T21:23:21Z","board_verified":true,"closed_at":null,"days_open":321,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":319},"description":"Role Description\nWe are seeking an experienced machine learning engineer to join our seasoned founding team to drive the development and innovation of our ML platform. Ideal candidates bring extensive experience in building the next generation of machine learning models and its training and serving infrastructure for the Spector.\nThis role requires a hands-on engineer who is passionate about our mission, thrives in a startup environment, and is committed to pushing the boundaries of what ML and GenAI can achieve in industrial resilience.\nYou will:\nCreate ML models which help drive value for users and our company.\n\nBuild scalable ML model training and serving infrastructure.\n\nEvaluate the technical tradeoffs of every decision.\n\nPerform code reviews and ensure exceptional code quality.\n\nIterate quickly without compromising quality.\n\nMust Have:\nBachelor's Degree in a relevant technical field such as computer science and 3+ years of post-Bachelor’s machine learning experience; or Master’s degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years of post-grad machine learning experience.\n\nExperience developing machine learning models for supervised, unsupervised, ranking, or other relevant applications of machine learning.\n\nStrong understanding of machine learning approaches and algorithms.\n\nExperience working with machine learning frameworks such as TensorFlow, PyTorch, Spark ML, scikit-learn, or related frameworks.\n\nAbility to work with both internal and external partners.\n\nStrong collaboration and mentorship skills.\n\nEntrepreneurial Mindset: Highly self motivated and adaptable with a passion for innovation, problem-solving, and making a meaningful impact in a startup environment.\n\nWillingness to take ownership and drive projects from concept to implementation.\n\nPreferred to have:\nExperience in on-prem ML model deployment and observability.\n\nExperience in building and deploying ML models for real time time series data like sensor/IoT data.\n\nAboutSpector.ai\nSpector.ai is a well-funded, fast-paced, innovative seed-stage startup focused on a mission to solve the $1.5 trillion challenge of industrial asset reliability. Spector is building an AI-first industrial agent platform designed to transform plant reliability and performance from reactive to autonomous operations. By combining machine learning and domain-specific industrial AI Agents, Spector.ai enables real-time diagnostics, root cause analysis, and actionable recommendations at scale. The platform extracts insights from complex industrial data including unstructured documentation and live sensor streams reducing false positives, shortening time to resolution, and scaling expertise without reliance on data scientists.\nWe are rapidly growing and looking for an experienced, self-driven DevOps Engineer to join our core team. 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