{"id":2585606,"url":"https://alion.io/job/berry-ai-machine-learning-team-lead","title":"Machine Learning Team Lead","company":{"id":2593136,"name":"Berry AI","domain":"berry-ai.com","url":"https://alion.io/company/berry-ai","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Taipei, Taiwan"],"countries":["TW"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":27000,"max_usd":66000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1119},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"Edge AI","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"LLM","optional":true},{"name":"Model Distillation","optional":true},{"name":"Multimodal AI","optional":true},{"name":"ONNX","optional":true},{"name":"OpenVINO","optional":true},{"name":"Quantization","optional":true},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-09-16T03:08:27Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-10-15T15:33:44Z","board_verified":true,"closed_at":null,"days_open":29,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":29},"description":"Berry AI builds AI-powered operations platforms for QSR restaurants - drive-thru analytics, loss prevention, and store management tooling deployed at thousands of locations across the US - and growing. Computer vision sits at the core of what we ship: models running on in-store edge devices, reading video in real restaurant conditions to understand vehicles, people, queues, and operational events. We're hiring a Machine Learning Team Lead to own that technical direction and lead the ML/CV team behind it.\nWhat you'll work on\nLead and grow the ML/CV team - set technical direction, own execution quality and delivery, mentor engineers, and own hiring - while staying hands-on.\n\nOwn the CV capabilities behind the product - object detection, multi-object tracking, person/vehicle Re-ID, camera calibration and geometric vision, and event recognition.\n\nWork with Product to turn customer problems into well-defined ML problems - the success metric and a roadmap the team can actually execute.\n\nDrive the full ML lifecycle - data collection, annotation strategy, training, evaluation, deployment, monitoring, and the iteration loop that keeps accuracy climbing after launch.\n\nPush performance under real-world conditions - occlusion, low light, lens distortion, camera movement, viewpoint variation, and domain shift across thousands of stores.\n\nGuide model optimization for constrained edge hardware - balancing accuracy against latency, throughput, memory, and operational reliability.\n\nBuild reusable pipelines and tooling that take manual effort out of data prep, store configuration, camera calibration, validation, and rollout.\n\nYou're a strong fit if you have\n7+ years in machine learning, deep learning, or computer vision, with a track record of shipping production CV systems - not just research prototypes.\n\nExperience leading an ML team, serving as technical lead, or owning the direction and delivery of a major ML product.\n\nReal depth in one or more of object detection, multi-object tracking, person/vehicle Re-ID, segmentation, or video understanding.\n\nA strong classical CV and image-processing foundation - feature extraction and matching, geometric transformations, interpolation, and image warping.\n\nThe judgment to evaluate CV systems under real-world conditions - occlusion, truncated objects, low light, motion blur, camera variation, domain shift - and to tell which failure modes actually matter to customers.\n\nEnd-to-end ML product lifecycle experience, from dataset development and training through production deployment and monitoring.\n\nPython and PyTorch or TensorFlow, with a solid grasp of model evaluation, error analysis, dataset quality, and experiment design.\n\nThe ability to turn ambiguous product needs into measurable objectives and executable plans, work across functions, and stay technically hands-on while leading the team.\n\nBonus points\nCamera geometry and calibration - pinhole camera models, intrinsic and extrinsic parameters.\n\nEdge AI and on-device inference - TensorRT, ONNX, OpenVINO, NVIDIA Jetson, DeepStream - plus quantization, pruning, distillation, or other inference optimization techniques.\n\nMLOps experience - dataset and model versioning, experiment tracking, automated evaluation, model monitoring, and progressive rollout.\n\nCV in uncontrolled physical environments - autonomous driving, robotics, security, industrial inspection, or smart retail.\n\nMultimodal models, VLMs, or LLM-based workflows used in real production systems.\n\nStartup or fast-scaling product org experience, or working with international teams and enterprise customers.\n\nOur engineering culture\nSmall team, high ownership, fast feedback from customers - and the operational rigor to make that velocity sustainable. Modern AI tooling - LLMs, coding agents, agent-driven workflows - is a normal part of how we work, and you're encouraged to push on what these tools can do.\n============================\nInterview Process\nOnline (Google Meet)\nVP Engineering Interview (1 hr)\n\nOnsite\nTechnical Interview (2.5 hrs)\nPre-read: sent ahead of time (see notes below)\n\nCEO & VP Interview (1.5 hrs)\n\nHR Interview (0.5 hr)\n\nNotes: Pre-read sent days before onsite as the basis for the Technical Interview discussion. No written submission needed, just come ready to talk through your thoughts.","description_format":"text","description_chars":4312,"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":[],"hiring_locations":[{"name":"Taiwan","iso":"TW","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-15T03:47:51Z"}],"visa":[],"liveness":{"score":38,"band":"fade","label":"Fading","p_open":1,"p_active":0.688,"p_room":0.55,"age_days":29,"expected_fill_days":24,"reasons":["conf:1","win:tail"],"computed_at":"2026-10-15T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/berry-ai-machine-learning-team-lead","json_url":"https://alion.io/job/berry-ai-machine-learning-team-lead.json","meta":{"generated_at":"2026-10-15T17:33:13Z","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":26564,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"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":2593136},"rest":"https://alion.io/mcp/rest/get_company?id=2593136"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fberry-ai-machine-learning-team-lead"},{"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%2Fberry-ai-machine-learning-team-lead"},{"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%2Fberry-ai-machine-learning-team-lead"},{"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/berry-ai-machine-learning-team-lead\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fberry-ai-machine-learning-team-lead"}]}