Data Science

Data Science Engineer Jobs

64 jobs found

Today

Machine Learning Engineer

Glint Tech Solutions LLC Sunnyvale, CA

Sunnyvale, CA

Today

Full time Ai Ml Automation Azure Ml

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Job Description

Glint Tech Solutions LLC is seeking an experienced Machine Learning Engineer to design, deploy, and scale ML models and pipelines, build ML infrastructure on cloud platforms, and collaborate with data science and engineering teams. This onsite role is based in Sunnyvale, CA.

Responsibilities

Design and implement scalable ML models and end-to-end pipelines using Python and Java.
Develop and maintain ML infrastructure on Google Cloud Platform and Microsoft Azure.
Implement and manage containerized workloads with Kubernetes.
Ensure scalable and reliable operation of ML systems in production environments.
Collaborate across data science and software engineering teams.

Requirements

Extensive hands-on experience with Java and Python.
Demonstrated expertise with Google Cloud Platform and Microsoft Azure.
Hands-on experience with Kubernetes and container orchestration.
Solid understanding of scalability concepts and distributed systems.

Technologies

Python
Java
GCP
Azure
Kubernetes

Location

Sunnyvale, CA (onsite)

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1d ago

Machine Learning Engineer - Document Digitization (LLMs)-Vice President

JPMorganChase Jersey City, NJ

Jersey City, NJ

1d ago

$164k - $260k/yr Full time Ai Ml Amazon Eks Artificial Intelligence

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Job Description

Senior Vice President level Machine Learning Engineer focused on designing, building, and deploying AI powered document digitization solutions using large language models to transform document processing and governance.

Responsibilities

Lead end-to-end design, development, and integration of AI powered document digitization solutions to extract data and insights from diverse document formats.
Manage the full AI/ML lifecycle: training, validation, deployment, monitoring, and ongoing improvements in production environments.
Apply generative AI and LLMs to automate and optimize document workflows.
Build and maintain scalable document digitization pipelines using Python, AI frameworks, and cloud technologies.
Provision and manage cloud resources with infrastructure as code tools (Terraform) and AWS services (SageMaker, Bedrock).
Ensure scalability, reliability, security, and governance compliance of AI/ML solutions.
Collaborate with cross functional teams to reimagine legacy document processing with generative AI and LLMs.
Develop and maintain dashboards and reporting tools to monitor digitization accuracy, workflow efficiency, and business impact.
Mentor junior engineers and promote best practices across AI/ML, software engineering, and testing.
Conduct model validation, human in the loop review, and implement continuous improvement strategies for digitization accuracy.
Contribute to communities of practice and explore new and emerging technologies.

Requirements

Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or related field, with relevant industry experience.
Strong proficiency in Python for building production grade AI services and data/document pipelines.
Strong working proficiency in Java, including API and microservice development with Spring Boot; familiarity with front end technologies (React.js, AngularJS) is a plus.
Hands-on experience delivering LLM powered GenAI applications in production (document understanding, retrieval augmented generation, workflow automation), including evaluation, observability, guardrails, and continuous improvement.
Experience with MLOps / LLMOps practices in production (CI/CD, automated testing, deployment strategies, monitoring, incident response).
Working knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning) with emphasis on integrating models into scalable systems.
Experience with AWS and cloud native delivery including SageMaker and/or Bedrock, containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
Familiarity with NoSQL / search / graph technologies (MongoDB Atlas, Elasticsearch/OpenSearch, Neo4j) for document search and knowledge retrieval.
Experience with agentic coding approaches, autonomous/assisted code agents, orchestration patterns, and tool-use/agent frameworks to accelerate document digitization workflows.
Strong understanding of SDLC, CI/CD, resiliency, and security practices; proven problem solving, communication, and collaboration skills.
Proven ability to accelerate development using AI technologies while maintaining engineering rigor (testing, code quality, governance).

Technologies

Python
Terraform
AWS SageMaker
AWS Bedrock
Docker
Kubernetes
Amazon EKS
Java
Spring Boot
React.js
AngularJS
TensorFlow
PyTorch
Scikit-learn
PyTorch Lightning
MongoDB Atlas
Elasticsearch/OpenSearch
Neo4j
LLMs

Benefits

Equity/stock-based compensation
Competitive base salary
Commission-based pay and/or discretionary incentive compensation
Comprehensive health care coverage
On-site health and wellness centers
Retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching

About Us

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

About the Team

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

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3d ago

Data Analyst & AI Engineering

Metrocast Cable Systems Quincy, MA

Quincy, MA

3d ago

$30 - $33/hr Full time Python Analyst Analytics

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Job Description

Hybrid Data Analyst and AI Engineering role at Metrocast Cable Systems in Quincy, MA, offering USD 30-33 per hour.

Responsibilities

Aggregate and sanitize large, heterogeneous datasets from multiple sources to maintain data quality and integrity, ensuring data is consistently clean and ready for analysis.
Conduct thorough data analyses to identify trends, patterns, and correlations that inform strategic decisions.
Create and maintain dashboards and reports using data visualization tools to communicate findings clearly to stakeholders.
Support the design, development, and deployment of machine learning models and AI algorithms.
Assist with training, validation, and evaluation of AI systems to ensure they meet performance benchmarks.
Collaborate with engineering and product teams to embed AI powered solutions into the company's services.
Produce comprehensive reports and presentations that clearly communicate analytical results and recommendations.
Stay current with evolving industry trends and advancements in data analytics and artificial intelligence.

Requirements

Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.
Proven experience in a data analysis role with a solid grounding in statistical principles.
Proficiency in SQL for querying and shaping data.
Strong programming skills in Python or R, including experience with data analysis libraries such as Pandas and NumPy.
Familiarity with machine learning concepts and core AI frameworks like Scikit-learn, TensorFlow, or PyTorch.
Experience using data visualization tools such as Tableau or Power BI.
Excellent analytical and problem-solving abilities with keen attention to detail.
Strong written and verbal communication skills, able to explain complex technical concepts to non-technical audiences.
Proactive, collaborative mindset with a demonstrated passion for data-driven innovation.

Technologies

SQL
Python
R
Pandas
NumPy
Scikit-learn
TensorFlow
PyTorch
Tableau
Power BI

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3d ago

Lead Machine Learning Engineer

Capital One McLean, VA

McLean, VA

3d ago

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

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Job Description

Capital One is seeking a Lead Machine Learning Engineer to join an onsite team in McLean, Virginia. The role focuses on productionizing ML applications and systems at scale, architecting solutions, developing and reviewing code, and maintaining high availability and performance within an Agile environment. The position offers an annual salary range of USD 197,300 to 225,100.

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 choices using knowledge of modeling techniques, including model selection, data and feature choices, 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 for state of the art big data and ML applications
Retrain, maintain, and monitor models in production
Utilize 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 code quality and governance, manage risk, and align ML practices with responsible and explainable AI standards
Work with 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

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

Benefits

Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Health benefits
Financial benefits
Other benefits

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3d ago

Analytics Engineer - AI Trainer

DataAnnotation Lincoln, NE 🇺🇸 Remote

Lincoln, NE

3d ago

$50 - $100/hr Full time Ai Ml Ai Training Analyst

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Job Description

DataAnnotation offers a fully remote Analytics Engineer - AI Trainer role with a flexible schedule and meaningful impact on AI systems that reason about data. You will assess AI generated quantitative work for technical accuracy, design problems to train and benchmark models, and document your analyses to advance quantitative reasoning in AI. This position is remote and open to residents in the United States, Canada, the United Kingdom, Ireland, Australia, and New Zealand.

Benefits

Fully remote work from anywhere within the United States, Canada, UK, Ireland, Australia, or New Zealand.
Flexible schedule that lets you choose projects and timing.
Competitive hourly pay, with opportunities for higher-paying projects based on performance, up to $60 per hour.
Direct impact on the development of AI systems designed for data analysis and quantitative reasoning.
Payment processed via PayPal.

Responsibilities

Assess AI generated quantitative work for technical accuracy and real world validity, including statistical analysis, predictive modeling, scientific reasoning, and data driven insights.
Design and solve quantitative problems used to train and benchmark AI systems across forecasting, experimental analysis, optimization, and statistical inference.
Write clear technical explanations and maintain well documented analytical code.
Provide feedback that shapes the next generation of AI models built for quantitative reasoning.

Requirements

2+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related fields.
Some coding experience with comfort writing and reviewing analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experimental design (A/B testing, hypothesis testing, regression, time series forecasting).
Fluency in English with strong writing skills (native or bilingual).
Bachelor's degree in a quantitative field is preferred; a master's or PhD is a plus.
Relevant credentials are advantageous (for example Kaggle rankings, AWS or GCP ML certifications, or equivalent demonstrated expertise).

Note: Payment is processed via PayPal. This role is available to applicants in the United States, Canada, the United Kingdom, Ireland, Australia, and New Zealand.

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4d ago

Senior Machine Learning Engineer - News

Disney Entertainment and ESPN Product & Technology New York, NY

New York, NY

4d ago

$149k - $199k/yr Full time Artificial Intelligence AWS Big Data

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Job Description

The Senior Machine Learning Engineer for News will shape the News ML Platform and build scalable ML infrastructure to enable real-time content personalization and targeted distribution across ABC News, Good Morning America, and local stations. This role collaborates with product, data, and engineering teams to drive algorithmic innovation and deliver scalable, personalized guest experiences.

Responsibilities

Lead complex technical initiatives end-to-end, from design through production deployment and ongoing operations
Design and build infrastructure supporting the full ML lifecycle, including data pipelines, workflow orchestration, data discovery and quality tooling, and feature libraries
Develop data- and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, autogenerated tagging solutions, and RAGs
Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions
Strategically prioritize initiatives and technical workstreams to maximize impact and address time-sensitive needs, while proactively identifying and mitigating risks to ensure successful execution
Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response
Mentor engineers, fostering ownership, collaboration, and continuous improvement
Contribute to technical documentation and promote knowledge sharing across teams

Requirements

Bachelor’s degree in Computer Science, Information Systems, Statistics, Math, or a comparable field of study, and/or equivalent work experience
5+ years of experience building and operating ML engineering systems in production environments
Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems
Comfort operating across the predictive stack, including data collection, data analysis, feature engineering, batch training, and low-latency online serving
Experience designing and developing backend microservices for large-scale distributed systems using REST
Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
Familiarity with developing and deploying Spark and ML pipelines
Hands-on experience with big data technologies such as Databricks, Kinesis, Kafka
Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team toward achieving business goals
Experience with observability tools for metrics, logging, and monitoring such as Datadog
Experience working in Agile/Scrum development environments
Excellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment

Technologies

REST
AWS
Step Functions
Lambda
Glue
SQS
SNS
Personalize
Spark
Databricks
Kinesis
Kafka
Datadog

Location

New York, NY (onsite)

Salary

USD 148,700 - 199,400 per yearly

Benefits

bonus and/or long-term incentive units
medical benefits
financial benefits
other benefits

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4d ago

Analytics Engineer - AI Trainer

DataAnnotation Winter Park, FL 🇺🇸 Remote

Winter Park, FL

4d ago

$50 - $100/hr Full time Ai Ml Ai Training Analyst

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Job Description

DataAnnotation is seeking an Analytics Engineer - AI Trainer to join a remote-friendly team focused on improving AI-driven quantitative reasoning. This role centers on evaluating AI-generated analyses for accuracy, designing problems to train and benchmark AI systems, and delivering clear, well-documented feedback to steer the next generation of quantitative AI models. The position offers a flexible schedule and remote work options, with a base connection to Winter Park, Florida.

Responsibilities

Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity.
Design and solve quantitative problems used to train and benchmark AI systems, spanning forecasting, experimental analysis, optimization, and statistical inference.
Write clear technical explanations and well-documented analytical code.
Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning.

Requirements

2+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related fields.
Some coding experience required, with comfort writing and reviewing analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting).
Fluency in English (native or bilingual level) with strong writing skills.
Bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus.
Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise).

Technologies

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: choose which projects you take on and when you work.
Competitive pay: projects are paid hourly, up to 60 USD per hour. Opportunities for higher-paying projects are available with strong performance.
Impact: help shape the future of AI systems built to reason about data and analytics.

Compensation

Hourly rate: USD 50 - 100

Note

Payment is made via PayPal. We will never ask for money from you.
This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand.