Machine Learning Engineer
for headings. Use - for lists,
for prose. No job title heading. No Job ID. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Also remove "Your Job" heading? The posting starts with "Your Job The ML Engineer will...". We need to preserve substantive info.
Let's parse content:
First paragraph: "Your Job The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre-screening candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle."
Second: "Our Team Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You'll join the platform team behind our Azure AI/ML engineering tools, partnering closely with data scientists, LLM engineers, and MLOps teams to keep GPU-heavy training and simulation workloads reliable and fast."
Third: "What You Will Do Design and train surrogate models (neural networks, Gaussian processes, gradient-boosted trees, GNNs/PINNs) on Azure GPU compute (ND/NC series). Incorporate physics-informed constraints so predictions stay physically valid, not just statistically fit. Build model-uncertainty and confidence scoring to decide which designs need full simulation validation, then retrain as new results arrive. Deploy and version models via Azure ML endpoints and model registry; monitor for drift on a rolling basis. Benchmark surrogate vs. full-simulation speedup to guide platform-level performance tuning."
Fourth: "Who You Are (Basic Qualifications) Extensive hands-on experience building, training, and deploying ML models in production — not just using pretrained APIs. 10+ years building ML for physical/engineering systems (surrogate modeling, physics-informed ML, or scientific ML). Strong Python with PyTorch or TensorFlow. Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain. Experience with Azure Machine Learning or a similar cloud ML platform. Familiarity with uncertainty quantification (Bayesian approaches, ensembling)."
Fifth: "What Will Put You Ahead Direct experience with industry-standard EM or physics simulation tools. Geometric deep learning (graph neural networks, mesh-based models) for CAD data. Background in RF/high-speed electronics or interconnect design."
Sixth: "For this role, we anticipate paying $170,000 - $250,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form. At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy."
Seventh: "Hiring Philosophy All Koch companies value diversity of thought, perspectives, aptitudes, experiences, and backgrounds. We are Military Ready and Second Chance employers. Learn more about our hiring philosophy here."
Eighth: "Who We Are As a Koch company, Molex is a leading supplier of connectors and interconnect components, driving innovation in electronics and supporting industries from automotive to health care and consumer to data communications. The thousands of innovators who work for Molex have made us a global electronics leader. Our experienced people, groundbreaking products and leading-edge technologies help us deliver a wider array of solutions to more markets than ever before. At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company."
Ninth: "Our Benefits Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength - focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes - medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. Specific eligibility criteria is set by the applicable Summary Plan Description, policy or guideline and benefits may vary by geographic region. If you have questions on what benefits apply to you, please speak to your recruiter. Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results."
Then there is "Equal Opportunities Equal Opportunity Employer, including disability and protected veteran status. Except where prohibited by state law, some offers of employment are conditioned upon successfully passing a drug test. This employer uses E-Verify. Please click here for additional information. (For Illinois E-Verify information click here, aquí, or tu)." This is boilerplate, remove.
Also "If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy." That's part of compensation section; we can keep but it's maybe boilerplate? It's about compensation philosophy; we can keep as part of Pay section.
We need sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule.
We need to map content.
"About the role": Could be the first two paragraphs describing job and team.
"Responsibilities": "What You Will Do" list.
"Requirements": maybe "Who You Are (Basic Qualifications)" as requirements.
"Qualifications": maybe "What Will Put You Ahead" as preferred qualifications.
"Skills": Could combine technical skills? Might be redundant. Could list skills from requirements: Python, PyTorch/TensorFlow, Azure ML, etc. But we should avoid thin sections. Perhaps we can omit Skills if not distinct.
"Benefits": from "Our Benefits".
"Pay": from compensation paragraph.
"Schedule": Not mentioned; no schedule info, so omit.
We must not create sections with placeholder text. So omit Schedule.
Also need to avoid duplication.
Let's craft HTML.
We'll have:
About the role
... combine first two paragraphs.
Responsibilities
- ... each bullet from What You Will Do.
Requirements
- ... each bullet from Who You Are (Basic Qualifications).
Qualifications
- ... each bullet from What Will Put You Ahead.
Benefits
... benefits paragraph.
Pay
... compensation paragraph (maybe trimmed to keep substantive).
We need to ensure we don't include boilerplate like "If you have questions, please speak to your recruiter..." maybe keep as part of Pay? It's about compensation philosophy; could be considered part of Pay but it's generic. Might be considered boilerplate. The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The compensation philosophy statement is not exactly those categories, but could be considered generic. However it's part of the compensation description; maybe keep it as it's substantive about compensation flexibility. I'd keep it.
Also need to remove "Hiring Philosophy", "Who We Are" sections as they are not requested headings; but we could incorporate into About the role? The instruction: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text. It didn't say we must include all possible sections; we can omit sections like About the role if we have content. We have content for About the role (job description and team). So we include.
We should not include "Hiring Philosophy" or "Who We Are" as separate headings because they are not in the list of allowed headings? The allowed headings list includes About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we should not add extra headings like Hiring Philosophy or Who We Are. So we omit those.
Thus we will not include those paragraphs.
Now craft content.
About the role paragraph: combine first two paragraphs.
First: "Your Job The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre-screening candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle."
Second: "Our Team Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You'll join the platform team behind our Azure AI/ML engineering tools, partnering closely with data scientists, LLM engineers, and MLOps teams to keep GPU-heavy training and simulation workloads reliable and fast."
We can combine into one or two paragraphs. Use for prose.
Responsibilities bullets:
- Design and train surrogate models (neural networks, Gaussian processes, gradient-boosted trees, GNNs/PINNs) on Azure GPU compute (ND/NC series).
- Incorporate physics-informed constraints so predictions stay physically valid, not just statistically fit.
- Build model-uncertainty and confidence scoring to decide which designs need full simulation validation, then retrain as new results arrive.
- Deploy and version models via Azure ML endpoints and model registry; monitor for drift on a rolling basis.
- Benchmark surrogate vs. full-simulation speedup to guide platform-level performance tuning.
Requirements bullets (from Who You Are):
- Extensive hands-on experience building, training, and deploying ML models in production — not just using pretrained APIs.
- 10+ years building ML for physical/engineering systems (surrogate modeling, physics-informed ML, or scientific ML).
- Strong Python with PyTorch or TensorFlow.
- Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain.
- Experience with Azure Machine Learning or a similar cloud ML platform.
- Familiarity with uncertainty quantification (Bayesian approaches, ensembling).
Qualifications bullets (What Will Put You Ahead):
- Direct experience with industry-standard EM or physics simulation tools.
- Geometric deep learning (graph neural networks, mesh-based models) for CAD data.
- Background in RF/high-speed electronics or interconnect design.
Benefits paragraph: from Our Benefits.
We need to keep the list: medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance.
We can keep as a paragraph.
Pay paragraph: combine compensation info.
"For this role, we anticipate paying $170,000 - $250,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form. At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy."
We can keep that.
Now ensure no duplicated lines. Also remove any mention of "If you have questions, please speak to your recruiter" maybe okay.
Now produce HTML fragment.
We must not include markdown code fences. Just raw HTML.
Let's craft.
for prose. No job title heading. No Job ID. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Also remove "Your Job" heading? The posting starts with "Your Job The ML Engineer will...". We need to preserve substantive info. Let's parse content: First paragraph: "Your Job The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre-screening candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle." Second: "Our Team Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You'll join the platform team behind our Azure AI/ML engineering tools, partnering closely with data scientists, LLM engineers, and MLOps teams to keep GPU-heavy training and simulation workloads reliable and fast." Third: "What You Will Do Design and train surrogate models (neural networks, Gaussian processes, gradient-boosted trees, GNNs/PINNs) on Azure GPU compute (ND/NC series). Incorporate physics-informed constraints so predictions stay physically valid, not just statistically fit. Build model-uncertainty and confidence scoring to decide which designs need full simulation validation, then retrain as new results arrive. Deploy and version models via Azure ML endpoints and model registry; monitor for drift on a rolling basis. Benchmark surrogate vs. full-simulation speedup to guide platform-level performance tuning." Fourth: "Who You Are (Basic Qualifications) Extensive hands-on experience building, training, and deploying ML models in production — not just using pretrained APIs. 10+ years building ML for physical/engineering systems (surrogate modeling, physics-informed ML, or scientific ML). Strong Python with PyTorch or TensorFlow. Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain. Experience with Azure Machine Learning or a similar cloud ML platform. Familiarity with uncertainty quantification (Bayesian approaches, ensembling)." Fifth: "What Will Put You Ahead Direct experience with industry-standard EM or physics simulation tools. Geometric deep learning (graph neural networks, mesh-based models) for CAD data. Background in RF/high-speed electronics or interconnect design." Sixth: "For this role, we anticipate paying $170,000 - $250,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form. At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy." Seventh: "Hiring Philosophy All Koch companies value diversity of thought, perspectives, aptitudes, experiences, and backgrounds. We are Military Ready and Second Chance employers. Learn more about our hiring philosophy here." Eighth: "Who We Are As a Koch company, Molex is a leading supplier of connectors and interconnect components, driving innovation in electronics and supporting industries from automotive to health care and consumer to data communications. The thousands of innovators who work for Molex have made us a global electronics leader. Our experienced people, groundbreaking products and leading-edge technologies help us deliver a wider array of solutions to more markets than ever before. At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company." Ninth: "Our Benefits Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength - focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes - medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. Specific eligibility criteria is set by the applicable Summary Plan Description, policy or guideline and benefits may vary by geographic region. If you have questions on what benefits apply to you, please speak to your recruiter. Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results." Then there is "Equal Opportunities Equal Opportunity Employer, including disability and protected veteran status. Except where prohibited by state law, some offers of employment are conditioned upon successfully passing a drug test. This employer uses E-Verify. Please click here for additional information. (For Illinois E-Verify information click here, aquí, or tu)." This is boilerplate, remove. Also "If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy." That's part of compensation section; we can keep but it's maybe boilerplate? It's about compensation philosophy; we can keep as part of Pay section. We need sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to map content. "About the role": Could be the first two paragraphs describing job and team. "Responsibilities": "What You Will Do" list. "Requirements": maybe "Who You Are (Basic Qualifications)" as requirements. "Qualifications": maybe "What Will Put You Ahead" as preferred qualifications. "Skills": Could combine technical skills? Might be redundant. Could list skills from requirements: Python, PyTorch/TensorFlow, Azure ML, etc. But we should avoid thin sections. Perhaps we can omit Skills if not distinct. "Benefits": from "Our Benefits". "Pay": from compensation paragraph. "Schedule": Not mentioned; no schedule info, so omit. We must not create sections with placeholder text. So omit Schedule. Also need to avoid duplication. Let's craft HTML. We'll have:
About the role
... combine first two paragraphs.
Responsibilities
- ... each bullet from What You Will Do.
Requirements
- ... each bullet from Who You Are (Basic Qualifications).
Qualifications
- ... each bullet from What Will Put You Ahead.
Benefits
... benefits paragraph.
Pay
... compensation paragraph (maybe trimmed to keep substantive).
We need to ensure we don't include boilerplate like "If you have questions, please speak to your recruiter..." maybe keep as part of Pay? It's about compensation philosophy; could be considered part of Pay but it's generic. Might be considered boilerplate. The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The compensation philosophy statement is not exactly those categories, but could be considered generic. However it's part of the compensation description; maybe keep it as it's substantive about compensation flexibility. I'd keep it. Also need to remove "Hiring Philosophy", "Who We Are" sections as they are not requested headings; but we could incorporate into About the role? The instruction: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text. It didn't say we must include all possible sections; we can omit sections like About the role if we have content. We have content for About the role (job description and team). So we include. We should not include "Hiring Philosophy" or "Who We Are" as separate headings because they are not in the list of allowed headings? The allowed headings list includes About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we should not add extra headings like Hiring Philosophy or Who We Are. So we omit those. Thus we will not include those paragraphs. Now craft content. About the role paragraph: combine first two paragraphs. First: "Your Job The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre-screening candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle." Second: "Our Team Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You'll join the platform team behind our Azure AI/ML engineering tools, partnering closely with data scientists, LLM engineers, and MLOps teams to keep GPU-heavy training and simulation workloads reliable and fast." We can combine into one or two paragraphs. Usefor prose. Responsibilities bullets: - Design and train surrogate models (neural networks, Gaussian processes, gradient-boosted trees, GNNs/PINNs) on Azure GPU compute (ND/NC series). - Incorporate physics-informed constraints so predictions stay physically valid, not just statistically fit. - Build model-uncertainty and confidence scoring to decide which designs need full simulation validation, then retrain as new results arrive. - Deploy and version models via Azure ML endpoints and model registry; monitor for drift on a rolling basis. - Benchmark surrogate vs. full-simulation speedup to guide platform-level performance tuning. Requirements bullets (from Who You Are): - Extensive hands-on experience building, training, and deploying ML models in production — not just using pretrained APIs. - 10+ years building ML for physical/engineering systems (surrogate modeling, physics-informed ML, or scientific ML). - Strong Python with PyTorch or TensorFlow. - Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain. - Experience with Azure Machine Learning or a similar cloud ML platform. - Familiarity with uncertainty quantification (Bayesian approaches, ensembling). Qualifications bullets (What Will Put You Ahead): - Direct experience with industry-standard EM or physics simulation tools. - Geometric deep learning (graph neural networks, mesh-based models) for CAD data. - Background in RF/high-speed electronics or interconnect design. Benefits paragraph: from Our Benefits. We need to keep the list: medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. We can keep as a paragraph. Pay paragraph: combine compensation info. "For this role, we anticipate paying $170,000 - $250,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form. At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy." We can keep that. Now ensure no duplicated lines. Also remove any mention of "If you have questions, please speak to your recruiter" maybe okay. Now produce HTML fragment. We must not include markdown code fences. Just raw HTML. Let's craft.