{"id":4143936,"url":"https://alion.io/job/emergence-senior-researcher-formal-methods","title":"Senior Researcher (Formal Methods)","company":{"id":23917,"name":"Emergence","domain":"emergence.ai","url":"https://alion.io/company/emergence","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","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":["Bengaluru, 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":"AI Agents","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"World Models","optional":false},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-11-12T04:57:25Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-15T21:27:37Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About us - Emergence AI is a frontier agentic AI lab advancing safe, autonomous AI through its pioneering neuroformal architecture. We are building the next generation of enterprise AI: systems capable of understanding complex knowledge, reasoning across information, executing multi-step workflows, and taking action with the verifiability and reliability required for mission-critical environments.\nOur Enterprise Agent Platform provides the foundation for building, deploying, and operating AI systems in production - from data connectivity and knowledge management to workflow orchestration, observability, evaluation, and governance. We partner with organizations in semiconductor manufacturing, life sciences, and other data-intensive industries to solve complex challenges that require trusted AI systems capable of operating in real-world environments.\nOur team brings experience from leading AI research labs and technology companies, including IBM Research, The Allen Institute for AI, Amazon, and Broadcom. With headquarters in New York and offices across California, Spain, and India, we bring together diverse expertise and perspectives to tackle some of the most challenging problems in enterprise AI.\nThe Role - We are looking for exceptional researchers and engineers to help define how intelligent systems are built when verification is a first-class primitive. You will design systems whose reasoning is not only powerful but also formally structured, machine-checkable, and composable across agents. \nAt the heart of the role is bridging theory and systems: taking ideas from formal methods, logic, and machine learning and turning them into end-to-end systems that reason, act, and improve over time. This is a high-ownership, high-intensity role for people who are as comfortable with abstraction as with implementation. \nWHAT YOU WILL DO \nAdvance the foundations of verifiable AI through new approaches in formal verification for AI, agentic reasoning and planning, and neuro-symbolic or neuro-formal architectures that integrate learning with structure. \nDesign formal representations, such as domain-specific languages, ontologies, and semantic layers, that make reasoning explicit, structured, and machine-verifiable, including the invariants, constraints, and proof obligations that define correct behavior. \nBuild end-to-end pipelines that turn natural language and data into formal specifications, validated with theorem provers, SAT-based constraint solving, and model checking. \nDesign the verification control layer: the interface that connects generative AI systems to formal validation and enforcement. \nBuild multi-agent systems in which correctness is compositional, defining how tasks break down into verifiable units, how delegation is structured, and how global guarantees hold across interacting agents. \nExplore causal reasoning, simulation, and world models to enable more reliable decision-making and scientifically grounded reasoning. \nShape our research direction through publications, open-source systems, and internal platform development. \nWHAT YOU BRING \nA Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Electrical Engineering, or a related discipline. We welcome exceptional candidates at every career stage. \nA solid foundation in one or more of machine learning, formal methods, programming languages, symbolic logic, or systems. \nDepth of understanding, clarity of thought, and the ability to make progress on hard, poorly defined problems. We look beyond credentials. \nThe ability to quickly internalize new abstractions and reason rigorously about them. \nComfort with ambiguity and a knack for imposing structure on it, moving fluidly between theory and implementation with a strong bias toward building. \nNICE TO HAVE \nExperience with LLM-based agents, theorem provers (e.g., Lean, Rocq), or constraint-solving frameworks is valuable. Evidence of excellence, whether through research, open-source contributions, competitive achievements, or impactful systems, is a strong signal. \nEmergence AI is an equal opportunity employer committed to building an inclusive workplace where people with diverse backgrounds, experiences, and perspectives can do their best work. We believe building trustworthy AI requires diverse ways of thinking, and we're committed to creating an environment where everyone can thrive.\nIf you're excited about this opportunity but don't meet every qualification, we encourage you to apply. 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