{"id":165934,"url":"https://alion.io/job/tower-research-capital-machine-learning-research-engineer","title":"Machine Learning Research Engineer","company":{"id":58857,"name":"Tower Research Capital","domain":"tower-research.com","url":"https://alion.io/company/tower-research-capital","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":32,"ghost_share":0,"stale_share":0.625,"repost_share":0,"time_to_fill_p50_days":84,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Dask","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Ray","optional":false},{"name":"TensorFlow","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2026-08-11T02:22:43Z","employer_posted_date":"2026-08-17","last_verified_at":"2026-10-17T17:34:36Z","board_verified":true,"closed_at":null,"days_open":67,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":67},"description":"Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.\nTower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. \nEngineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.\nAt Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do - combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.\nAt Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.\nSummary:\nAs an AI/ML Applied Research Engineer, you will sit at the cutting-edge intersection of our central machine learning infrastructure and our research teams. Your core mandate is to act as \"Customer Zero\" for our internal ML Research platform.\nYou will focus on expanding our ML research platform to benchmark, rapidly prototype, and stress-test both software and hardware layers across our entire distributed ML stack. By leveraging AI agents and auto-research capabilities, you will push our systems to their limits, identify bottlenecks, and create a frictionless environment to test novel machine learning models on realistic, large-scale data.\nUltimately, by hands-on testing these systems yourself, you will act as a technical advisor. You will share insights on research progress, evaluate how new ideas fare in practice, and help guide the strategic direction of our central engineering efforts.\nResponsibilities:\nPlatform Validation & Infrastructure Benchmarking: \nServe as the primary feedback loop for the entire ML stack. \nActively run complex models through our full ML pipeline to comprehensively test both the training and inference environments.\nValidate the central infrastructure in practice, seeing exactly how new research ideas fare and identifying system bottlenecks before broader rollout to research teams.\nStreamline Rapid Prototyping for ML Research:\nBuild high-level abstractions that allow users to bypass setup friction. \nIntegrate our core ML tooling directly with our underlying simulation and data frameworks, providing a unified entry point to access our full tech stack. \nEnable rapid iteration on real-world data and seamless distributed training via Ray.\nAgentic Workflows for ML Research: \nLeverage AI agents and auto-research workflows to autonomously generate experiments, stress-test our distributed clusters, and provide data-driven, actionable feedback on what infrastructure needs to be optimized or built next.\nResearch Platform Feedback & Insights Sharing: \nAct as the critical bridge between infrastructure builders and ML researchers. \nBe the first to exhaustively test new models and push the platform's limits.\nDocument and publish empirical findings on system capabilities and hardware performance. \nTake your validated insights to assist engineering teams with platform improvements and advise researchers on how to best leverage the stack.\nQualifications:\nStrong Software Engineering Foundation: \nDeep proficiency in Python and software design principles. \nAbility to build clean, scalable APIs and abstractions that other developers and researchers are enthusiastic about using.\nApplied Machine Learning: \nHands-on experience with modern frameworks (PyTorch, TensorFlow, etc.) \nStrong practical understanding of how to train, evaluate, and deploy models at scale.\nDistributed Compute: \nExperience scaling ML workloads across GPUs and multi-node clusters using frameworks like Ray, Dask, or PyTorch Distributed.\nAI Agent Workflows: \nFamiliarity with LLM tooling, agentic frameworks, and using AI to automate coding, research, or testing tasks.\nSystem Profiling & Optimization: \nAbility to debug and identify bottlenecks across hardware and software layers (e.g., memory limits, GPU utilization, data pipeline latency).\nNice to Have:\nPrevious experience working in quantitative finance or complex algorithmic research environments.\nFamiliarity with large-scale time-series data, simulation engines, or performance benchmarking.\nA proven track record of bridging the gap between systems engineering and applied machine learning research.\nAnticipated annual base salary range $200,000-$300,000, plus eligible for discretionary bonus.\nTower’s headquarters are in the historic Equitable Building, right in the heart of NYC’s Financial District and our impact is global, with over a dozen offices around the world.\n At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive - without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.\nOur benefits include:\nGenerous paid time off policies\nSavings plans and other financial wellness tools available in each region\nHybrid working opportunities\nFree breakfast, lunch, and snacks daily\nIn-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)\nCompany-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)\nVolunteer opportunities and charitable giving\nSocial events, happy hours, treats, and celebrations throughout the year\nWorkshops and continuous learning opportunities\nAt Tower, you’ll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work - together.\nTower Research Capital is an equal opportunity employer.","description_format":"text","description_chars":6609,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Hybrid work"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Hedge Funds & Alternative Investments"],"lifecycle":[{"event":"open","at":"2026-08-11T02:22:43Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 54 · green card filings: 12","filings_12m":54,"filings_prev_12m":27,"green_card_filings_12m":12,"median_offered_wage_usd":147045,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":15}],"liveness":{"score":32,"band":"fade","label":"Fading","p_open":1,"p_active":0.534,"p_room":0.6,"age_days":67,"expected_fill_days":84,"reasons":["conf:0","stale_co","velocity","win:late","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":300000,"is_top_pay":true},"html_url":"https://alion.io/job/tower-research-capital-machine-learning-research-engineer","json_url":"https://alion.io/job/tower-research-capital-machine-learning-research-engineer.json","meta":{"generated_at":"2026-10-17T18:36:29Z","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":1438,"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":58857},"rest":"https://alion.io/mcp/rest/get_company?id=58857"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Ftower-research-capital-machine-learning-research-engineer"},{"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%2Ftower-research-capital-machine-learning-research-engineer"},{"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%2Ftower-research-capital-machine-learning-research-engineer"},{"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/tower-research-capital-machine-learning-research-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Ftower-research-capital-machine-learning-research-engineer"}]}