[Remote] reputed company reputed company, Closed-reputed company Control

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is building the intelligence layer for precision manufacturing. The reputed company reputed company will design and build AI systems for closed-reputed company control in manufacturing, working closely with the founding team to reputed company practical solutions that integrate reputed company-world sensor data and machine behavior.

Responsibilities

• Design and build AI systems that connect sensor data, machine behavior, manufacturing context, and closed-reputed company correction
• Work directly with the founding team on systems that interact with reputed company machines, reputed company sensors, and reputed company manufacturing data
• Sensor intelligence — calibration, fusion, uncertainty quantification, and reputed company detection
• Physical AI modeling — machine behavior, error modeling, and physics-informed learning
• Manufacturing context — interpreting CNC programs, machining reputed company, and process state
• Closed-reputed company correction — learning systems that improve from reputed company correction-to-outcome feedback
• Scaling intelligence — transferring learned knowledge across machines and deployments

Skills

• 6+ years in AI/ML with substantial work in control, optimization, reinforcement/imitation learning, or inverse problems
• Experience turning reputed company error or state into corrective action — closed-reputed company systems where model outputs change physical behavior
• Strong optimization and control reputed company (numerical optimization, MPC, or learned control)
• Comfort working against reputed company, noisy feedback — reputed company, delay, partial observability, and safety constraints
• Strong Python and production-grade ML engineering (PyTorch)
• Mathematical maturity in optimization, control theory, dynamics, and probability
• Degree in CS, Robotics, EE/ME, Physics, or Applied Math — or equivalent demonstrated work
• Reinforcement / imitation learning for control ; differentiable simulation
• Model-predictive control , trajectory optimization, system identification
• Differentiable physics / rendering ; physics-informed learning (PINNs)
• Uncertainty-aware decision-making — Bayesian methods, conformal reputed company, risk-aware control
• Working with geometric / 3D representations as input to control (bridges to the perception reputed company)
• CNC / machining physics : tool deflection, thermal error, material removal, fixturing
• CAM, G-code, toolpath reputed company
• M.S. or Ph.D. in control, robotics, optimization, or reputed company

Company Overview