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Lead / Principal Process ML Engineer

DHD Consulting ◆

Onsite · San Diego, CA, US

Pay not listedFull-Time

Easy applyPosted Jul 23

Job ID 872881via WorkOnward

Accounting Specialist

DHD Consulting ◆

Onsite · Plainview, TX, 79072, US

$70kFull-Time

Easy applyPosted Jul 23

Job ID 887023via WorkOnward

Customer Quality & Complaint Specialist

DHD Consulting ◆

Onsite · Jersey City, NJ, US

$70k–$75kFull-Time

Easy applyPosted Jul 23

Job ID 645897via WorkOnward

Customer Service Engineer (Vision System)

DHD Consulting ◆

Onsite · Niles, OH, US

Pay not listedFull-Time

Easy applyPosted Jul 22

Job ID 133791via WorkOnward

EHS Manager (Environmental, Health & Safety)

DHD Consulting ◆

Onsite · Gainesville, GA, US

$90k–$110kFull-Time

Easy applyPosted Jul 22

Job ID 131913via WorkOnward

Accounting Manager (Junior Level)

DHD Consulting ◆

Onsite · Shelbyville, TN, US

Pay not listedFull-Time

Easy applyPosted Jul 22

Job ID 920005via WorkOnward

Quality Control Specialist

DHD Consulting ◆

Onsite · Shelbyville, TN, US

Pay not listedFull-Time

Easy applyPosted Jul 22

Job ID 272315via WorkOnward

Quality Assurance Specialist

DHD Consulting ◆

Onsite · Shelbyville, TN, US

Pay not listedFull-Time

Easy applyPosted Jul 22

Job ID 198641via WorkOnward

Sales Specialist

DHD Consulting ◆

Onsite · Shelbyville, TN, US

Pay not listedFull-Time

Easy applyPosted Jul 22

Job ID 283423via WorkOnward

Purchasing Specialist

DHD Consulting ◆

Onsite · Shelbyville, TN, US

Pay not listedFull-Time

Easy applyPosted Jul 22

Job ID 561619via WorkOnward

DHD Consulting ◆

Lead / Principal Process ML Engineer

Location: Onsite · San Diego, CA, US
Job type: Full-Time
Pay: Pay not listed
Department: IT & Technology
Posted: Jul 23

Job ID 872881via WorkOnward

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Overview

We are building AI platforms that run on real factory floors, predicting, optimizing, and controlling manufacturing processes in real time. This role is needed to expand our process optimization capability — we need a technical leader who can own the full lifecycle of ML-driven process optimization products, from causal modeling to productization and customer deployment. Currently there is no dedicated technical lead for this product area, and growing customer demand requires a senior leader to set the technical vision and drive execution.
Roles and Responsibilities
Own the technical direction for key projects — set vision, define what to build, manage priorities, and be accountable for delivery
Lead development of ML-driven process optimization products — from causal modeling to productization and customer deployment
Make architecture decisions: select modeling approaches, define system boundaries, and evaluate trade-offs between physical fidelity, inference speed, and product constraints
Define modeling strategy — decide which physics to encode, which architectures to use, and how to validate against real process data
Drive architecture reviews and technical decision-making across the process optimization team
Hire, mentor, and grow engineers — build a high-performing team through hiring, code reviews, and technical coaching
Coordinate across HQ (Seoul) and overseas R&D labs — aligning research with product roadmaps across time zones
Own production-grade delivery — models must run reliably inside equipment operating 24/7 on customer lines

Requirements

Doctorate (Ph.D.)
Mechanical Engineering, Physics, Computer Science, Electrical Engineering, or a related field
8+ years of industry experience post-Ph.D.
Proven track record of shipping process optimization or control products from problem definition through customer-facing deployment
Experience leading a technical team — setting direction, managing delivery, and making architecture decisions
Strong physics foundation (fluid dynamics, thermodynamics, heat transfer, mechanics)
Strong ML skills (PyTorch, custom architectures, PINNs, neural operators, surrogate models)
Ability to bridge physics and product — translate process understanding into model design and product features
Comfort with ambiguity: able to define the problem and the approach, not just execute a spec
Experience shipping ML-driven process optimization or control products in an industry setting
Experience leading or managing a technical team (ML or applied science)
Experience with production software systems — ML integration, data pipelines, deployment infrastructure
Preferred Requirements
Prior role as Tech Lead, Staff Engineer, or Team Lead in an ML or applied science team
Experience productizing process optimization as a commercial product deployed on customer sites
Hands-on manufacturing process experience — semiconductor, SMT, electronics assembly, or precision manufacturing
Experience coordinating technical direction across distributed teams (HQ + overseas R&D)
Published work in scientific machine learning, computational physics, or neural operators
Experience with SPC, Cpk analysis, or 3D inspection/metrology systems

Benefits

Health/Dental/Vision/Life Insurance at no employee premium (including dependent coverage)
401K retirement plan with 5% matching
Generous PTO and paid holidays

Benefits

sponsorship