Machine Learning Engineer 3

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. No Job ID. Remove boilerplate like EEO, legal, etc. Must preserve all substantive info. We need to parse the posting. Content: Intro paragraph: "Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One." That's about the role. Then "What You’ll Do:" list of duties. Then "Basic Qualifications:" list. Then "Preferred Qualifications:" list. Then immigration note: "At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, ...)." This is not a section we need to include; maybe we can drop as it's not requested. Then salary info: "The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $161,800 - $184,600 for Machine Learning Engineer 3 New York, NY: $176,500 - $201,400 for Machine Learning Engineer 3 Plano, TX: $147,100 - $167,900 for Machine Learning Engineer 3 Richmond, VA: $147,100 - $167,900 for Machine Learning Engineer 3 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan." That's Pay section. Then benefits: "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." That's Benefits. Then "This role is expected to accept applications for a minimum of 5 business days. No agencies please." That's maybe not needed. Then EEO etc. Remove. We need sections: About the role (intro), Responsibilities (What You’ll Do), Requirements (Basic Qualifications?), Qualifications (Preferred Qualifications?), Skills (maybe combine? but we can include Skills if there is specific content; there is mention of programming languages, frameworks, etc. Could be part of Requirements. But we can create a Skills section listing languages, frameworks, etc. However we must not invent sections without content. The posting includes programming languages like Python, Scala, or Java under Basic Qualifications? Actually it's under "Use programming languages like Python, Scala, or Java" in responsibilities. Also frameworks: PyTorch, Tensorflow, libraries Pandas, NumPy, Scikit-learn. Also Spark, Ray, Kubernetes, AWS/GCP/Azure. So we could create a Skills section with those. But we already have Requirements (Basic Qualifications) and Qualifications (Preferred). Might be overlapping. The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can include those that have content. We need to decide what goes where. About the role: intro paragraph. Responsibilities: the bullet list under "What You’ll Do:" (the list of duties). We'll convert each bullet to

. Requirements: Basic Qualifications list. Qualifications: Preferred Qualifications list. Skills: maybe we can extract specific technical skills from responsibilities and qualifications? But we might duplicate. However we can still create a Skills section listing programming languages, frameworks, tools, etc. But we must not invent content; we can pull from the text. The posting includes: "Use programming languages like Python, Scala, or Java", "ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation", "Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment", "Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications", "Retrain, maintain, and monitor models in production", "Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models", "Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code", "Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI". Also qualifications list many. Thus we can create Skills section summarizing: Programming languages: Python, Scala, Java; ML frameworks: PyTorch, TensorFlow; Libraries: Pandas, NumPy, Scikit-learn; Distributed systems: Spark, Ray; Cloud platforms: AWS, GCP, Azure; Orchestration: Kubernetes; CI/CD, testing, source control, code reviews; ML techniques: supervised, unsupervised, reinforcement learning; model types: regression, classification, clustering; architectures: RNN, CNN, LSTM, Transformer; concepts: loss function, hyperparameters, regularization; evaluation: model accuracy, underfitting/overfitting; data pipelines; pre-production testing, deployment techniques, monitoring, alarms, incident response. We must ensure we only include content that appears. All those appear somewhere. Now Benefits: we have paragraph about benefits. Pay: we have salary ranges and incentive compensation. Schedule: Not mentioned. So we should not include Schedule section. Now we need to output only HTML fragment, no /, no markdown fences. We'll produce something like:

About the role

...

Responsibilities

• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
...

Requirements

• Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
...

Qualifications

• Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
...

Skills

• Programming languages: Python, Scala, Java
...

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

Pay

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $161,800 - $184,600 for Machine Learning Engineer 3; New York, NY: $176,500 - $201,400 for Machine Learning Engineer 3; Plano, TX: $147,100 - $167,900 for Machine Learning Engineer 3; Richmond, VA: $147,100 - $167,900 for Machine Learning Engineer 3. Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

We must ensure we didn't include any boilerplate like EEO, legal, accommodation, etc. Also we removed "No agencies please." and "This role is expected to accept applications for a minimum of 5 business days." Not needed. Check that we didn't repeat job title as heading. Good. Now ensure we didn't include any placeholder like "commensurate with experience". Not present. Now produce final HTML. Let's craft the lists precisely. Responsibilities bullets from text: - Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams - Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation - Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment - Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications - Retrain, maintain, and monitor models in production - Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models - Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code - Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Note: The last bullet includes "Use programming languages like Python, Scala, or Java". Actually that sentence appears after the bullet list? In the text: "Use programming languages like Python, Scala, or Java". It's separate line after the bullet list? Actually after the bullet list there is "Use programming languages like Python, Scala, or Java". It might be part of responsibilities. We'll include as a bullet. Thus add bullet: "Use programming languages like Python, Scala, or Java". Now Requirements (Basic Qualifications) bullets: - Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) - At least 3 years of experience programming with Python, Java, Golang, or C++ - At least 2 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) - At least 3 years of experience using and operating large scale distributed systems (Spark, Ray)