... CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film ... process conditions via generative or adjoint/topology-optimization methods. • Build bi ...
... CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film ... process conditions via generative or adjoint/topology-optimization methods. • Build bi ...
Ald Process Engineer information
See Florida salary details
$37K - $43.3K
2% of jobs
$43.3K - $49.6K
9% of jobs
$55.4K is the 25th percentile. Wages below this are outliers.
$49.6K - $55.9K
15% of jobs
$55.9K - $62.3K
18% of jobs
The median wage is $64.4K / yr.
$62.3K - $68.6K
17% of jobs
$68.6K - $74.9K
14% of jobs
$75.1K is the 75th percentile. Wages above this are outliers.
$74.9K - $81.2K
11% of jobs
$81.2K - $87.5K
6% of jobs
$87.5K - $93.9K
4% of jobs
$93.9K - $100.2K
3% of jobs
$100.2K - $106.5K
1% of jobs
$37K
$68.8K
$106.5K
How much do ald process engineer jobs pay per year?
As of May 29, 2026, the average yearly pay for ald process engineer in Florida is $68,764.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,700.00 and $77,000.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as an ALD Process Engineer, and why are they important?
To thrive as an ALD Process Engineer, you need a solid background in chemical engineering, materials science, or a related field, often with experience in thin film deposition and semiconductor manufacturing. Familiarity with atomic layer deposition (ALD) tools, process characterization techniques, and statistical process control systems is typically required. Analytical thinking, problem-solving abilities, and effective communication skills help professionals excel in cross-functional teams and troubleshoot complex processes. These competencies are crucial for optimizing production yield, ensuring process reliability, and advancing technology in high-precision manufacturing environments.
What are some common challenges faced by ALD Process Engineers in optimizing thin film deposition?
ALD Process Engineers often encounter challenges related to achieving uniform film thickness and conformality across complex wafer topographies. Fine-tuning process parameters like temperature, precursor pulse times, and purge sequences is critical to prevent issues such as particle contamination or incomplete reactions. Additionally, collaborating closely with equipment engineers and R&D teams is essential to troubleshoot process deviations and implement improvements. Staying updated on the latest ALD chemistries and tool capabilities also helps address evolving production requirements.
What are ALD Process Engineers?
ALD Process Engineers are professionals who specialize in Atomic Layer Deposition (ALD), a thin-film deposition technique used in semiconductor manufacturing and other industries. They develop, optimize, and monitor ALD processes to ensure precise control of film thickness and composition at the atomic level. These engineers work closely with equipment, materials, and design teams to improve device performance and yield. Their role involves troubleshooting process issues, scaling up production, and implementing new technologies in fabrication environments.
What is the difference between Ald Process Engineer vs Chemical Process Engineer?
| Aspect | Ald Process Engineer | Chemical Process Engineer |
|---|---|---|
| Credentials | Bachelor's in Chemical Engineering or related field; often requires process-specific certifications | Bachelor's or higher in Chemical Engineering; similar certification requirements |
| Work Environment | Industrial plants, manufacturing facilities, chemical processing plants | Refineries, chemical manufacturing, research labs |
| Industry Usage | Primarily in chemical, petrochemical, and refining industries | Broader, including pharmaceuticals, food processing, and chemicals |
The Ald Process Engineer and Chemical Process Engineer roles share similar educational backgrounds and work environments, often overlapping in chemical and petrochemical industries. While both focus on process optimization and safety, the Ald Process Engineer may specialize more in specific refining processes, whereas the Chemical Process Engineer has a broader scope across various chemical sectors.
What are popular job titles related to Ald Process Engineer jobs in Florida? For Ald Process Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Ald Process Engineer jobs in Florida look for? The top searched job categories for Ald Process Engineer jobs in Florida are:
What cities in Florida are hiring for Ald Process Engineer jobs? Cities in Florida with the most Ald Process Engineer job openings:
Contractor
Posted 16 days ago
Job description
**Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
MSP Owner: Deepa Narayanan
Location: Santa Clara CA
Duration: 6 Months
Gbams Number: 10680928
ONSITE ROLE
Local candidates preferred.
Ai Hardware Design Engineer
***NOTE: Experience for SciML R&D and exposure in Neural operators, PINNs etc. is required***
We are seeking an Ai Hardware Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and workflows for applications such as content creation, product design, and intelligent automation.
• Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film-uniformity, step-coverage, particle behavior, and thermal outcomes.
• Implement inverse-design workflows where target performance specifications generate feasible chamber geometries, showerhead/baffle designs, and process conditions via generative or adjoint/topology-optimization methods.
• Build bi-directional models that infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
• Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
• Platform & MLOps Infrastructure: Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments to deploy models efficiently.
• Develop robust multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.
• Collaborate with physicists, domain experts, and software engineers to validate that AI models comply with fundamental scientific laws.
•
Required Skills & Qualifications
• Education: Master's or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or related field.
• Technical Expertise:
o Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
o Experience with generative AI (LLMs, diffusion models, graph-based models).
o Knowledge of computational materials methods (DFT, MD, phase-field modeling).
• Additional Skills:
o Familiarity with MLOps, HPC environments, and cloud deployment.
o Proven experience (code repos, publications) bridging simulation software, hardware design, and ML.
Skills: Digital : Python~Digital : Machine Learning
Experience Required: 6-8, Project Code :
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
MSP Owner: Deepa Narayanan
Location: Santa Clara CA
Duration: 6 Months
Gbams Number: 10680928
ONSITE ROLE
Local candidates preferred.
Ai Hardware Design Engineer
***NOTE: Experience for SciML R&D and exposure in Neural operators, PINNs etc. is required***
We are seeking an Ai Hardware Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and workflows for applications such as content creation, product design, and intelligent automation.
• Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film-uniformity, step-coverage, particle behavior, and thermal outcomes.
• Implement inverse-design workflows where target performance specifications generate feasible chamber geometries, showerhead/baffle designs, and process conditions via generative or adjoint/topology-optimization methods.
• Build bi-directional models that infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
• Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
• Platform & MLOps Infrastructure: Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments to deploy models efficiently.
• Develop robust multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.
• Collaborate with physicists, domain experts, and software engineers to validate that AI models comply with fundamental scientific laws.
•
Required Skills & Qualifications
• Education: Master's or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or related field.
• Technical Expertise:
o Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
o Experience with generative AI (LLMs, diffusion models, graph-based models).
o Knowledge of computational materials methods (DFT, MD, phase-field modeling).
• Additional Skills:
o Familiarity with MLOps, HPC environments, and cloud deployment.
o Proven experience (code repos, publications) bridging simulation software, hardware design, and ML.
Skills: Digital : Python~Digital : Machine Learning
Experience Required: 6-8, Project Code :
About Real Soft
Sourced by ZipRecruiter
Industry
It services
Company size
501 - 1,000 Employees
Headquarters location
Monmouth Junction, NJ, US
Year founded
1991