Algorithm Developer IV

for prose. Remove boilerplate. Let's parse content. We have location & compensation: Location: Redmond, WA; Work Arrangement: Hybrid, approx 3 days onsite per week as needed; Pay Rate: $91/hour; Experience Level: Entry to Mid-Level; Years of Experience: 1-6 years; Education: Bachelor's degree in Computer Science, Mathematics, Engineering, or related field required/preferred; Master's degree preferred. Then plain-language summary: This role sits on the Sensors & Systems Team, which develops prototypes using sensor data, machine learning, and hardware platforms. The team works on collecting data from sensors, training machine learning models, optimizing performance, and deploying those models onto hardware devices. This Is An Applied Machine Learning Role That Combines Machine LearningDeep LearningAlgorithm DevelopmentPython DevelopmentHardware DeploymentEmbedded SystemsSensor Data ProcessingRobotics Prototyping Then "What They'll Be Doing Core Responsibilities" list. Then "Must-Have Qualifications Technical Skills" list. Then Education (already listed earlier but repeated). Might combine. Then "Preferred Qualifications" list. We need sections: About the role (maybe plain-language summary), Responsibilities, Requirements (or Qualifications), Skills, Benefits, Pay, Schedule. We have Pay Rate: $91/hour. Work Arrangement: Hybrid, approx 3 days onsite per week as needed => schedule. Benefits: none mentioned. We should not create sections with placeholder text. So include Pay and Schedule sections if we have info. We have location maybe as metadata; could be in a short p. We must not repeat job title as heading. We must not include Job ID etc. We need to preserve all substantive info. Let's structure:

Location: Redmond, WA

Work Arrangement: Hybrid, approximately 3 days onsite per week as needed

Pay Rate: $91/hour

About the role

This role sits on the Sensors & Systems Team, which develops prototypes using sensor data, machine learning, and hardware platforms. The team works on collecting data from sensors, training machine learning models, optimizing performance, and deploying those models onto hardware devices. This is an applied machine learning role that combines machine learning, deep learning, algorithm development, Python development, hardware deployment, embedded systems, sensor data processing, and robotics prototyping.

Responsibilities

• Train and optimize machine learning and hybrid AI pipelines for hardware deployment.
• Develop advanced deep learning algorithms and techniques.
• Design, implement, and test machine learning models.
• Build statistical models to analyze workload and system performance.
• Convert business and customer requirements into algorithm designs.
• Troubleshoot software and algorithm-related issues.
• Improve software and model performance.
• Deploy machine learning algorithms to hardware platforms.
• Work with sensor-generated data to support prototype development.
• Collaborate with teams developing sensors, wired systems, and robotics solutions.

Requirements

• Python
• Machine Learning Algorithms
• Deep Learning experience
• PyTorch and/or TensorFlow
• Algorithm development experience
• Experience training, testing, and optimizing ML models
• Understanding of AI-assisted development tools such as: ChatGPT, Claude
• Ability to work independently and manage projects autonomously
• Bachelor's degree in Computer Science, Mathematics, Engineering, or related field
• Master's degree preferred

Requirements

(list of Must-Have Qualifications Technical Skills + Education + ability to work independently)

Preferred Qualifications

(list of Embedded Systems Experience, Hardware & Deployment Experience, Additional Technical Skills)

Pay

$91/hour

Schedule

Hybrid, approximately 3 days onsite per week as needed

for section headings. Use

• for lists. Use

  for prose. We must not include markdown fences. Output only HTML fragment. Let's craft. Check for any boilerplate: "Plain-Language Summary" heading we turned into About the role. "What They'll Be Doing Core Responsibilities" turned into Responsibilities. "Must-Have Qualifications Technical Skills" turned into Requirements. "Preferred Qualifications" turned into Preferred Qualifications. Education already in Requirements. We need to ensure we didn't miss any specifics: The line "This Is An Applied Machine Learning Role That Combines Machine LearningDeep LearningAlgorithm DevelopmentPython DevelopmentHardware DeploymentEmbedded SystemsSensor Data ProcessingRobotics Prototyping" we incorporated into About the role. Also note "Experience Level: Entry to Mid-Level" and "Years of Experience: 1-6 years". Should we include? Could be part of Requirements or a separate p. Since not captured elsewhere, we should include. Could add to Requirements list as items: Entry to Mid-Level experience, 1-6 years of experience. Or we could add a short p after location. Let's add to Requirements as list items. Also "Education: Bachelor's degree in Computer Science, Mathematics, Engineering, or related field required/preferred; Master's degree preferred" we have. Now ensure we didn't include any fluff like "commensurate with experience". Not present. Now produce HTML. Let's write:

  Location: Redmond, WA

  Work Arrangement: Hybrid, approximately 3 days onsite per week as needed

  Pay Rate: $91/hour

  About the role

  This role sits on the Sensors & Systems Team, which develops prototypes using sensor data, machine learning, and hardware platforms. The team works on collecting data from sensors, training machine learning models, optimizing performance, and deploying those models onto hardware devices. This is an applied machine learning role that combines machine learning, deep learning, algorithm development, Python development, hardware deployment, embedded systems, sensor data processing, and robotics prototyping.

  Responsibilities

  • Train and optimize machine learning and hybrid AI pipelines for hardware deployment.
  • Develop advanced deep learning algorithms and techniques.
  • Design, implement, and test machine learning models.
  • Build statistical models to analyze workload and system performance.
  • Convert business and customer requirements into algorithm designs.
  • Troubleshoot software and algorithm-related issues.
  • Improve software and model performance.
  • Deploy machine learning algorithms to hardware platforms.
  • Work with sensor-generated data to support prototype development.
  • Collaborate with teams developing sensors, wired systems, and robotics solutions.

  Requirements

  • Python
  • Machine Learning Algorithms
  • Deep Learning experience
  • PyTorch and/or TensorFlow
  • Algorithm development experience
  • Experience training, testing, and optimizing ML models
  • Understanding of AI-assisted development tools such as: ChatGPT, Claude
  • Ability to work independently and manage projects autonomously
  • Bachelor's degree in Computer Science, Mathematics, Engineering, or related field
  • Master's degree preferred
  • Entry to Mid-Level experience
  • 1-6 years of experience

  Preferred Qualifications

  • Embedded Systems Experience: Raspberry Pi, NVIDIA Jetson, FPGA platforms
  • Hardware & Deployment Experience: Deploying machine learning models to edge devices, hardware optimization, firmware deployment
  • Additional Technical Skills: C++, Object-Oriented Programming, ARM CPU/NPU architecture, firmware understanding, performance optimization

  Pay

  $91/hour

  Schedule

  Hybrid, approximately 3 days onsite per week as needed

  Check duplication: Pay appears twice (once in metadata p and in Pay section). Might be redundant but we need to preserve all info. The metadata p includes Pay Rate: $91/hour. The Pay section repeats same. Could we avoid duplication by not including Pay in metadata? The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it." So we can fold location, work arrangement, pay into short p's. Then we also have Pay and Schedule sections if posting actually states them. The posting does state Pay Rate and Work Arrangement. So we need Pay and Schedule sections. The metadata p could be just location and maybe work arrangement? But we need to preserve all info; we can include location in a p, and then have Pay and Schedule sections. Work arrangement could go in Schedule section. So we can have:

  Location: Redmond, WA

  Then Pay section:

  $91/hour

  Schedule section:

  Hybrid, approximately 3 days onsite per week as needed

  Thus we avoid duplicating pay. Let's do that. Thus final HTML:

  Location: Redmond, WA

  About the role

  ...