scikit-learn

scikit-learn Data Jobs

10 jobs found

5d ago

Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology)

Capital One New York, NY

New York, NY

5d ago

$251k - $286k/yr Full time Big Data Cloud Platforms Data Processing

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Job Description

Capital One’s Enterprise Platforms Technology (EPTech) group is seeking a Sr Lead, Machine Learning Engineer to scale ML initiatives from concept to production. In this role, you will design and operationalize machine learning models and the supporting infrastructure, while ensuring governance, security, and robust performance across systems. Based in New York City and focused on enterprise-scale solutions, this onsite position emphasizes collaboration with product and data science teams to solve real business problems through advanced analytics.

Responsibilities

Design, build, and deliver ML models and components that address real-world business challenges, in partnership with Product and Data Science teams.
Guide ML infrastructure decisions with a solid understanding of modeling techniques, data, features, training, hyperparameters, dimensionality, bias/variance, and validation.
Tackle complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Work within a cross-functional Agile team to create and enhance software for state-of-the-art big data and ML applications.
Retrain, maintain, and monitor models in production environments.
Utilize cloud-based architectures and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure code quality and governance, manage risk related to models, and follow responsible and explainable AI practices.
Program in Python, Scala, or Java.

Requirements

Bachelor’s degree
At least 8 years designing and building data-intensive solutions using distributed computing (internships excluded)
At least 4 years programming with Python, Scala, or Java
At least 3 years building, scaling, and optimizing ML systems
At least 2 years leading teams developing ML solutions

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS
Azure
Google Cloud Platform

Benefits

Health benefits
Financial benefits
Performance-based incentive compensation (cash bonuses and long-term incentives)

Preferred Qualifications

Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
4+ years of on-the-job experience with industry recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
3+ years of developing performant, resilient, and maintainable code
3+ years of data gathering and preparation for ML models
3+ years of people management experience
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
3+ years building production-ready data pipelines that feed ML models
Ability to communicate complex technical concepts clearly to a variety of audiences

Salary and location

Location: New York, NY (onsite)

Salary: USD 250,800 - 286,200 per year

Salary ranges by location

McLean, VA: $229,900 - $262,400
New York, NY: $250,800 - $286,200

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23d ago

Machine Learning Engineer

Leidos Beavercreek, OH

Beavercreek, OH

23d ago

$87k - $157k/yr Full time Artificial Intelligence Deep Learning Engineering

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Job Description

Leidos seeks a mid-level Machine Learning Engineer for its Electronic Warfare Division, focusing on processing remote sensing data across SAR/RF, acoustic, EO/IR, and LIDAR modalities and advancing cross-sensor target recognition, onsite in Beavercreek, OH.

Responsibilities

Collaborate with engineering teams to research, design, and implement sensor exploitation platforms including signal processing, automatic target recognition (ATR), and target signature modeling.
Develop ATR algorithms in Python, MATLAB, and C++ for real world deployments, applying cutting edge AI and ML techniques to improve ATR performance.
Partner with customers to translate mission requirements into new capabilities and enhance existing systems.
Create performance models and algorithms for both new and existing target recognition solutions.
Engage in high level software development across Python, C++, and MATLAB, including design, implementation, troubleshooting, and debugging.
Demonstrate strong written and oral communication, producing software documentation for the customer and delivering presentations to the customer and the broader research community.

Requirements

Bachelor's degree with 4+ years of ML development experience or Master's degree with 2+ years; Doctorate in a technical field possible.
Active SECRET clearance or higher, with ability to obtain TS/SCI clearance.
U.S. citizenship required.
Advanced Python proficiency, including libraries such as XGBoost, PyTorch, and Scikit-Learn.
Experience in deep learning with one or more current large language models.
Strong written and verbal communication of technical solutions to colleagues and customers.
Familiarity with data processing tools such as NumPy, SciPy, and MATLAB for data evaluation and interpretation.
Experience with Linux and Windows operating systems.

Technologies

Python
MATLAB
C++
XGBoost
PyTorch
Scikit-Learn
NumPy
SciPy
Linux
Windows
GitLab
Jira

Benefits

competitive compensation
Health and Wellness programs
Income Protection
Paid Leave
Retirement

Job Details

Location: Beavercreek, OH (onsite)
Salary: USD 87,100 - 157,450 per year
Experience: 2+ years
Education: Bachelor’s or Master’s degree

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26d ago

Machine Learning Engineer II

Glidewell Dental Irvine, CA

Irvine, CA

26d ago

$122k - $160k/yr Full time Artificial Intelligence AWS Cloud

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Job Description

Glidewell Dental offers a comprehensive benefits package, an onsite Irvine workplace, and a diverse, collaborative culture designed to support professional growth. You’ll join a team that values practical ML solutions, thoughtful experimentation, and measurable impact, backed by strong wellness and family-friendly benefits.

Benefits

Medical, dental, and vision coverage
401(k) with company match
Company-paid life insurance
Paid time off including vacation, holidays, and sick days
Employee gym with fitness classes and a meditation room
On-site medical and wellness center offering massage therapy and acupuncture
Company-subsidized cafes and public internet cafes
Employee lounges with big screen TVs and game tables
Company-sponsored events and a diverse work environment with over forty nationalities represented
Employee discounts and a flexible spending account
Retirement plan with ongoing benefits

Responsibilities

Design, develop, and deploy machine learning models for real-world applications
Build scalable pipelines for data ingestion, pre-processing, training, and inference
Own end-to-end development of ML algorithms, including data analysis, feature engineering, model development, training, validation, and performance evaluation
Design, implement, and optimize retrieval-augmented generation pipelines that fuse large language models with vector search
Construct data ingestion and embedding pipelines to enable efficient indexing and retrieval
Fine-tune and adapt LLMs for domain-specific tasks via instruction tuning, prompt engineering, and low-rank adaptation techniques
Engage in both engineering and research to explore cutting-edge ML methods and architectures to boost retrieval and generation performance
Collaborate with stakeholders to translate business requirements into robust technical solutions with measurable impact
Partner with engineering teams to scale and advance ML initiatives across the organization
Identify new opportunities to apply ML to improve business workflows and processes
Develop a deep understanding of Glidewell's products, data, and customers to deliver impactful solutions
Contribute to related duties and projects as business needs require

Requirements

Master's degree in Machine Learning, Deep Learning, or a computer science related field; PhD preferred
Minimum three years of relevant work experience, or equivalent education/experience
Strong grasp of fundamental ML concepts, practices, and procedures
Experience with data discovery, data aggregation, and feature engineering using SQL
Experience training, evaluating, optimizing, deploying, and maintaining ML models in production
Ability to log, track, A/B test, and analyze performance of ML algorithms in production
Proficient Python development and a track record of building data-driven, scalable, reliable applications on AWS
Applied ML to a variety of optimization problems such as sales forecasting, recommendation systems, sentiment analysis, computer vision and NLP, clustering, and object detection
Experience with open-source ML/DL libraries including LangChain, HuggingFace, TensorFlow, scikit-learn, pandas, PyTorch, and Keras
Experience with relational, non-relational, and high-scale data processing/storage frameworks (SQL, AWS Redshift, Aurora, S3, DynamoDB, MySQL, PostgreSQL)
Experience with AWS Serverless architecture and native services such as Bedrock, EC2, Lambda, Step Functions, SageMaker, Rekognition, Comprehend, Lex/Polly, and Transcribe

Technologies

Python
Amazon Web Services (AWS)
LangChain
HuggingFace
TensorFlow
scikit-learn
pandas
PyTorch
Keras
SQL
AWS Redshift
AWS Aurora
AWS S3
DynamoDB
MySQL
PostgreSQL
AWS Bedrock
EC2
Lambda
Step Functions
SageMaker
Rekognition
Comprehend
Lex
Polly
Transcribe

Role details

Location: Irvine, CA, onsite
Job type: Full-time
Salary: USD 122,000 - 160,000 per year
Education: Master’s degree required
Experience: Minimum three years required
Work location: In person

Application questions

How many years of experience do you have with Amazon Bedrock?
Do you have experience deploying Machine Learning models from end to end?
Do you have experience with serverless deployment?
Will you now, or in the future, require sponsorship for employment visa status (e.g., H-1B visa status)?

Experience

Amazon SageMaker: 2 years (Required)
Python: 2 years (Required)

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30d ago

Lead Machine Learning Engineer (Enterprise Platforms Technology)

Capital One McLean, VA

McLean, VA

30d ago

$197k - $225k/yr Full time AWS Azure Big Data

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Job Description

This on-site role in McLean, VA focuses on productionizing ML applications and systems at scale within Capital One's Enterprise Platforms Technology group.

Responsibilities

Design, build, and deliver ML models and components that address real world business problems, in collaboration with Product and Data Science teams.
Inform ML infrastructure decisions through understanding of modeling techniques and issues, including model selection, data, feature engineering, 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 within 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 platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure code is well governed to minimize vulnerabilities, and that models meet risk and Responsible AI / Explainable AI standards.
Use programming languages such as Python, Scala, or Java.

Requirements

Bachelor’s Degree.
At least 6 years of experience designing and building data-intensive solutions with distributed computing (internship experience does not apply).
At least 4 years of experience programming with Python, Scala, or Java.
At least 2 years of experience designing, scaling, and optimizing ML systems.

Technologies

Python, Scala, Java
scikit-learn, PyTorch, Dask, Spark, TensorFlow
AWS, Azure, Google Cloud Platform

Benefits

Health benefits
Financial benefits
Performance-based incentive compensation (cash bonuses and/or long-term incentives)

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30d ago

Sr. Distinguished Machine Learning Engineer

Capital One McLean, VA

McLean, VA

30d ago

$315k - $359k/yr Full time Senior Cloud Architecture DevOps

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Job Description

Capital One offers a performance-based incentive program with cash bonuses and long-term incentives. This onsite, McLean, VA opportunity places you in a senior leadership role focused on bringing machine learning to production at scale. You will guide architecture and modeling efforts, oversee the development of robust ML systems, and mentor engineers across cross-functional teams.

Responsibilities

Deliver machine learning models and software components that address complex business problems in financial services, collaborating with Product, Architecture, Engineering, and Data Science teams.
Shape and advance ML models and supporting software to enable advanced, intelligent systems.
Lead large scale ML initiatives with the end user in mind.
Utilize cloud based architectures and technologies to deploy optimized ML models at scale.
Refine data pipelines to feed ML models efficiently.
Work with Python, Scala, and C or C++ across development tasks.
Leverage compute frameworks such as Dask and RAPIDS to accelerate processing.
Promote best practices across engineering and modeling lifecycles.
Contribute to recruiting, developing, and retaining top engineering talent.

Requirements

Bachelor’s degree.
At least 10 years designing and building data‑intensive solutions using distributed computing.
At least 7 years programming in C, C++, Python, or Scala.
At least 4 years of experience with the full ML development lifecycle in a business critical setting.

Technologies

Python
Scala
C/C++
Dask
RAPIDS
NumPy
Pandas
Scikit-learn

Benefits

Performance based incentive compensation (cash bonuses and/or long term incentives)

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30d ago

Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS)

Capital One Richmond, VA

Richmond, VA

30d ago

$179k - $205k/yr Full time AWS Big Data Cloud

Apply Now

Job Description

Capital One is seeking a Lead Machine Learning Engineer to scale ML solutions across the organization, focusing on architecture, model development, deployment, and operations within an Agile environment. This role centers on productionizing ML applications and systems, building robust data pipelines, and delivering ML capabilities at scale.

Location

Richmond, VA (onsite)

Compensation

Salary: USD 179,400 - 204,700 per year

Responsibilities

Design, build, and deliver ML models and components that address real-world business problems, partnering with Product and Data Science teams.
Inform ML infrastructure decisions using knowledge of modeling techniques, including model choice, data and feature selection, 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 within a cross-functional Agile team to create and improve software for state-of-the-art big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and code.
Ensure code quality and governance, manage risk for models, and adhere to Responsible and Explainable AI practices.
Use programming languages such as Python, Scala, or Java.

Requirements

Bachelor’s degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems

Technologies

KServe, Kubernetes, PyTorch, TensorFlow
AWS, Python, Scala, Java
scikit-learn, Dask, Spark

Benefits

This role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Incentives can be discretionary or non-discretionary depending on the plan.
Health, financial, and other benefits that support total well-being.

Team Description

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in res

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30d ago

Senior Machine Learning Engineer

Capital One McLean, VA

McLean, VA

30d ago

$162k - $185k/yr Full time AWS Azure Ml Deep Learning

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Job Description

Capital One offers a performance based incentive compensation, including cash bonuses and long term incentives, along with health, financial and other benefits. This onsite role in McLean, VA carries a salary range of USD 161,800 - 184,600 per year.

Responsibilities

Design, build, and deliver ML models and components that solve real world business problems, collaborating with Product and Data Science teams.
Inform ML infrastructure decisions using knowledge of modeling techniques, data and feature selection, model training, hyperparameter tuning, dimensionality, bias and variance, and validation.
Address complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Collaborate within a cross functional Agile team to create and enhance software powering state of the art big data and ML applications.
Retrain, maintain, and monitor models in production environments.
Leverage or build cloud based architectures, technologies, and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply 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 responsible and explainable AI practices.
Program in Python, Scala, or Java.

Requirements

Bachelor’s Degree
At least 4 years of experience programming with Python, Scala, or Java (internship experience does not apply)
At least 3 years of experience designing and building data intensive solutions using distributed computing
At least 2 years of on the job experience with industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
At least 1 year of experience productionizing, monitoring, and maintaining models