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senior lead software engineer

Metas Solutions

<div>Metas Solutions has an &quot;opening&quot; for a talented Senior Data Engineer based in Atlanta, GA. The ideal candidate must be able to work onsite in the Atlanta metro area and someone who's proficient in Databricks workspaces and Azure infrastructure. In this position, you'll drive the next generation of our analytics products by architecting and delivering end-to-end cloud analytics solutions. In a fully cloud-native environment, you'll partner with product managers, data scientists, software engineers, machine learning (ML) engineers and business analysts to enable and support a platform that powers personalized experiences and operational efficiency. You'll leverage automated model CI/CD, containerized deployments (Docker/Kubernetes), and real-time monitoring to ensure our ML systems are reliable, secure, and scalable.
You will be responsible for the design, implementation, and maintenance of the Databricks workspaces and its associated Azure infrastructure. You will manage and optimize data and machine learning workloads, ensuring a reliable, secure, and scalable platform for business analysts, data engineering and data science teams.
Responsibilities:<ul><li>
Lead the administration and governance framework of the platform regarding the security posture of the enterprise and its key stakeholders</li><li>
Design and implement automated solutions to streamline accounts and workspace administration</li><li>
Collaborate with cross-functional teams to understand business needs and translate them into ML solutions</li><li>
Mentor junior engineers and provide technical leadership in Databricks best practices and techniques</li><li>
Conduct cost and performance analysis of the various computes, and data assets within the platform</li><li>
Stay current with the latest advancements in Databricks SQL, Machine Learning and AI, and integrate new technologies and methods as applicable</li><li>
Engage in knowledge sharing and contribute to building a strong, collaborative team environment</li></ul>
Qualifications:<ul><li>
5+ years of experience with Databricks Account and Workspace Administration, including governance, configuration, and security management</li><li>
Experience with optimizing Databricks environments for cost efficiency, performance, and reliability</li><li>
Experience with developing and maintaining Databricks data pipelines using Autoloader, Delta Live Tables, and Databricks Workflows</li><li>
Experience with implementing MLOps solutions using MLflow 2.0/3.0, Serving Endpoints, and Model Registry in production environments</li><li>
Experience with Databricks SQL tools such as Queries and AI/BI Dashboards</li><li>
Experience with large datasets and distributed computing across cloud platforms (AWS, GCP, Azure), including Azure services like Entra ID, Data Factory, Key Vault, and Purview</li><li>
Knowledge of Unity Catalog Governance Architecture and enterprise data security best practices</li><li>
Possession of strong communication and documentation skills with the ability to clearly convey complex technical concepts to both technical and non-technical audiences</li><li>
Ability to work on-site in Atlanta, Georgia</li><li>
Master's degree in computer science, Computer Engineering, or related programs</li></ul>
Additional Qualifications:<ul><li>
Knowledge of Azure Cloud Networking concepts like VNET Injection</li><li>
Databricks Platform Administrator Certification</li><li>
Microsoft Certified: Azure Administrator Associate</li></ul>
Security Requirements:<ul><li>
Must be US Citizen and with the ability to obtain a US Government security clearance (Public Trust 5) within a reasonable period</li><li>
Market competitive salary, commensurate with experience and education</li><li>
Comprehensive benefits package available, Medical, Dental, Vision and Life Insurance, Paid Time Off (PTO), 401K with company match, growth, and promotion opportunities</li></ul>
We are an Equal Opportunity Employer/Veterans/Disabled</div>

Senior Data Engineer

The Home Depot

<div>Position Purpose:
The Machine Learning Engineer II is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. ML Engineers are expected to pair daily as they work through user stories and support products as they evolve. 
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering. 
ML Engineers should be able to operate independently with minimum guidance from others, although will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices. 
Key Responsibilities:<ul><li>
65% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do &quot;destructive testing&quot; to ensure adequate resiliency in production; Program configuration/modification and setup activities on large projects using HD approved methodology; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
15% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul> 

Direct Manager/Direct Reports:<ul><li>
This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul> 

Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 

Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 

Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.
</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 

Preferred Qualifications:<ul><li>
1 - 3 years of relevant work experience</li><li>
Experience in a modern scripting language (preferably Python)</li><li>
Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc</li><li>
Experience in modern web application framework such as Node.js</li><li>
Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3</li><li>
Experience in writing SQL queries against a relational database</li><li>
Experience in version control systems (preferable Git)</li><li>
Familiarity with algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Familiarity with basic statistics and regression algorithms</li><li>
Familiarity with advanced statistics such as bayesian statistics</li><li>
Familiarity with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.</li><li>
Familiarity with Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoML</li><li>
Familiarity with a Linux or Unix based environment</li><li>
Familiarity with a CI/CD toolchain</li><li>
Familiarity with REST and effective web service design</li><li>
Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li></ul> 

Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul> 

Preferred Education:<ul><li>
No additional education</li></ul> 

Minimum Years of Work Experience:<ul><li>
1</li></ul> 

Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 

Minimum Leadership Experience:<ul><li>
None</li></ul> 

Preferred Leadership Experience:<ul><li>
None</li></ul> 

Certifications:<ul><li>
None</li></ul> 

Competencies:<ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul></div>

Machine Learning Engineer II (Remote)

Powerplan

<div>Overview:

The Senior AI/ML Engineer will modernize and scale the company&rsquo;s enterprise data and AI platform by designing AI-ready data models, operationalizing ML systems, and enabling natural-language analytics through Databricks Genie or equivalent AI tooling.
This role exists to shift the organization from dashboard-driven analytics to AI-powered decision intelligence at enterprise scale.
Responsibilities:

Performance Objectives 
Modernize and Operationalize the Analytics Data Platform
Within 6&ndash;9 months, design and implement a scalable medallion-based architecture (Bronze/Silver/Gold) in Databricks or Snowflake that supports AI-ready datasets, improves query performance by 30%, and reduces data reliability incidents by 40%.
Subtasks:<ul><li>
Redesign analytical data models for AI/ML consumption</li><li>
Implement governance using Unity Catalog or Snowflake controls</li><li>
Optimize distributed compute performance</li><li>
Establish monitoring and quality validation checkpoints</li></ul> 
Enable AI-Ready Data Modeling &amp; Governance
Within 6 months, establish semantic models and metadata standards that enable business-facing AI querying with 95% data trust rating from stakeholders.
Subtasks:<ul><li>
Standardize schema design for ML and GenAI workloads</li><li>
Align business definitions with governed datasets</li><li>
Implement lineage and access controls</li><li>
Reduce duplicate or conflicting metric definitions</li></ul> 
Build and Deploy Production-Grade ML Pipelines
Within 9&ndash;12 months, implement reusable ML lifecycle pipelines (experimentation training evaluation deployment) that reduce time-to-production for ML models by 50%.
Subtasks:<ul><li>
Standardize MLflow/Feature Store workflows</li><li>
Implement CI/CD for ML</li><li>
Improve model observability and drift monitoring</li><li>
Establish model documentation standards</li></ul> 
Implement Natural Language AI Analytics (Databricks Genie Enablement)
Within 6 months, deploy and optimize Databricks Genie (or equivalent AI query interface) enabling business users to generate accurate plain-language insights with 80% adoption across target user groups.
Subtasks:<ul><li>
Translate business questions into semantic AI-ready datasets</li><li>
Improve response accuracy through model + metadata tuning</li><li>
Partner with Product on use-case prioritization</li><li>
Track and improve AI query accuracy and user engagement</li></ul> 
Democratize AI Across Business Teams
Within 12 months, embed AI-driven analytics into at least 3 core business workflows, demonstrating measurable business impact (e.g., cost reduction, revenue lift, or decision cycle time improvement).
Subtasks:<ul><li>
Identify high-value AI use cases</li><li>
Collaborate cross-functionally</li><li>
Deliver production-ready AI solutions</li><li>
Document business ROI outcomes</li></ul> 
Establish Enterprise AI Platform Standards
Within 12 months, define and institutionalize architectural standards, best practices, and governance frameworks adopted across Engineering and Analytics teams.
Subtasks:<ul><li>
Publish architecture reference patterns</li><li>
Lead design reviews</li><li>
Mentor engineers</li><li>
Influence long-term AI strategy</li></ul> 
Success Metrics Summary<ul><li>
30%+ performance improvement in analytics workloads</li><li>
40%+ reduction in data quality incidents</li><li>
50% reduction in ML deployment cycle time</li><li>
80% Genie adoption in target group</li><li>
3+ AI use cases with measurable ROI</li><li><ul><li>95% stakeholder trust in AI-generated insights</li></ul></li></ul>
Qualifications:

Growth &amp; Career Move
This is a high-impact platform leadership role enabling enterprise AI transformation. The individual will shape architecture standards, influence executive AI strategy, and lead the shift from traditional BI to AI-powered decision intelligence.
Required Qualifications<ul><li>
10+ years of experience in Data Analytics, Data Engineering, ML Engineering, or AI Engineering</li><li>
Strong hands-on experience with Databricks or Snowflake in production environments</li><li>
Expertise in SQL, Python, and distributed data processing (Spark preferred)</li><li>
Strong understanding of data modeling for analytics and AI</li><li>
Experience building and deploying ML models in real-world systems</li><li>
Familiarity with LLMs, GenAI concepts, and AI-assisted analytics</li><li>
Experience with ML lifecycle tools (MLflow, Feature Stores, CI/CD for ML)</li></ul><div></div><div> 
Preferred Qualifications</div><ul><li>
Direct experience with Databricks Genie or AI-powered BI tools</li><li>
Experience with Unity Catalog, Delta Live Tables, or Snowflake governance features</li><li>
Exposure to Azure, AWS, or GCP cloud platforms</li><li>
Experience working in regulated or enterprise SaaS environments</li><li>
Ability to explain complex technical concepts to non-technical stakeholders</li></ul><div></div><div> 
What Success Looks Like in This Role</div><ul><li>
Business users can ask questions in plain English and get trusted, accurate insights</li><li>
Data models are AI-ready, scalable, and well-governed</li><li>
ML models move smoothly from experimentation to production</li><li>
Databricks Genie adoption grows with measurable business impact</li><li>
AI is embedded into analytics not bolted on</li></ul><div></div><div> 
Why Join Us</div><ul><li>
Work on real AI/ML problems at enterprise scale</li><li>
Influence the evolution of a modern data + AI platform</li><li>
Partner with senior leaders shaping the company&rsquo;s AI-first future</li><li>
Build systems that turn data into decisions not dashboards</li></ul><div>
PowerPlan is an EOE</div><div>
Applicant Privacy Notice</div><div></div> 
Please note that this is a hybrid role that involves a combination of onsite work from our corporate office as well as work from home. While we strive to accommodate flexible working arrangements when sensible, there will be times when onsite work is required. This could include scheduled office days, team meetings, client meetings, or special events.</div>

Senior Databricks AI Engineer

<div>Position Purpose:
The Staff Machine Learning Engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. Staff ML Engineers are expected to pair daily as they work through user stories and support products as they evolve. 
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering. 
Staff ML Engineers will be a core player on the product team and are expected to build and grow skillsets of more junior engineers. You will also be able to drive multiple ML initiatives by directing algorithm and technology product design 
Key Responsibilities:<ul><li>
45% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions, Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
15% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations; Attends conferences and learns how to apply new innovations and technologies where appropriate</li><li>
20% Strategy and Planning - Researches and analyzes business trends and behavioral data to identify opportunities for improvement and new initiatives; Leads the evaluation development and recommendation of specific technology products and platforms to provide cost-effective solutions that meet business and technology requirements; Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products; Proactively creates and maintains tools for monitoring and support; Participates in project planning and management across multiple efforts; Develops formal training courses</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
3 - 6 years of relevant work experience</li><li>
Experience to algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Experience to basic statistics and regression algorithms</li><li>
Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li><li>
Experience in training machine learning models with extremely large datasets</li><li>
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.</li><li>
Experience with GPU acceleration (i.e. CUDA and cuDNN)</li><li>
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoML</li><li>
Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc</li><li>
Experience in a modern scripting language (preferably Python)</li><li>
Experience in modern web application framework such as Node.js</li><li>
Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3</li><li>
Experience in writing SQL queries against a relational database</li><li>
Experience in version control systems (preferable Git)</li><li>
Experience in a Linux or Unix based environment</li><li>
Experience in a CI/CD toolchain</li><li>
Experience in REST and effective web service design</li><li>
Experience in production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li><li>
Experience in NoSQL databases</li><li>
Experience in cloud computing platform and associated automation patterns and machine learning services they provide</li><li>
Experience in defensive coding practices and patterns for high Availability</li><li>
Experience in A/B testing and effective REST design for scalable web services architecture</li><li>
Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
3</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul></div>

Staff Machine Learning Engineer (Remote)

CVS Health

<div>We&rsquo;re building a world of health around every individual &mdash; shaping a more connected, convenient and compassionate health experience. At CVS Health&reg;, you&rsquo;ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger &ndash; helping to simplify health care one person, one family and one community at a time.
Position Summary
If you&rsquo;re eager to make a real impact in the health care industry through your own meaningful contributions, explore a role in technology with CVS Health. Our journey calls for technical innovators and data visionaries: come help us pave the way.
At CVS Health, we possess an extensive repository of healthcare data that spans over 150 million individuals, providing an unparalleled foundation for ambitious Data Engineers. In this role, you will engage with complex business challenges, harnessing modern tools and technologies to securely store, process, transform, and enrich terabyte to petabyte scale healthcare data. Your work will underpin data-driven business decisions and contribute to our mission of delivering industry-best data products / software with a customer-first mindset and team-oriented approach.
As a Senior Data Engineer, you will be instrumental in designing, developing, and maintaining optimal data pipelines to assemble large and intricate datasets, catering to the business requirements of various CVS lines of business. Collaborating closely with teams, you will craft tools to provide actionable insights and integrate them with consumer touchpoints.
In this role, you will:<ul><li>
Architect and develop robust, scalable ETL/ELT pipelines using Cloud Dataflow, Cloud composer (Airflow), and Pub/Sub for both batch and streaming use cases. Leverage BigQuery as the central data warehouse and design integrations with other GCP services (e.g., Cloud storage, Cloud functions).</li><li>
Build and optimize analytical data models in BigQuery. Implement partitioning, clustering, and materialized views for performance and cost efficiency. Ensure compliance with data governance, access controls, and IAM best practices.</li><li>
Develop integrations with external systems (APIs, flat files etc.) using GCP-native or hybrid approaches. Utiilize tools like Dataflow or custom Python/Java services on Cloud Functions or Cloud Run to handle transformations and ingestion logic.</li><li>
Build automated CI/CD pipeline using Cloud Build, GitHub Actions, or Jenkins for deploying data pipeline code and workflows. Set up observability using Cloud Monitoring, Cloud Logging, and Error Reporting to ensure pipeline reliability.</li><li>
Lead architectural decisions for data platforms and mentor junior engineers on cloud-native data engineering patterns. Promote best practices for code quality, version control, cost optimization, and data security in a GCP environment. Drive initiatives around data democratization, including building reusable datasets and data catalogs via Datapelx or Data Catalog.</li></ul>
As leaders in healthcare, our analytics and engineering teams deliver innovative solutions to business problems by collaborating with cross-functional teams in a dynamic and agile environment. You will be part of a team that values collaboration and encourages innovative thinking at all levels. You will be intellectually challenged to solve problems associated with large scale complex, structured and unstructured data, that will allow you to grow your technical skills and engineering expertise.
This role may work onsite 2 days a week in one of CVS Health's core hubs in: NYC, Hartford, CT or Wellesley, MA. Full-time Remote candidates will also be considered.
Required Qualifications<ul><li>
3+ years of experience with SQL, NoSQL</li><li>
3+ years of experience with Python (or a comparable scripting language)</li><li>
3+ years of experience with Data warehouses (such as data modeling and technical architectures) and infrastructure components</li><li>
3+ years of experience with ETL/ELT, and building high-volume data pipelines</li><li>
3+ years of experience with reporting/analytic tools</li><li>
3+ years of experience with Query optimization, data structures, transformation, metadata, dependency, and workload management</li><li>
3+ years of experience with Big data and cloud architecture</li><li>
3+ years of hands-on experience building modern data pipelines within a major cloud platform (GCP, AWS, Azure)</li><li>
3+ years of experience with deployment/scaling of apps on containerized environment (i.e. Kubernetes, AKS)</li><li>
3+ years of experience with real-time and streaming technology (i.e. Azure Event Hubs, Azure Functions, Kafka, Spark Streaming)</li><li>
1+ year(s) of soliciting complex requirements and managing relationships with key stakeholders</li><li>
1+ year(s) of experience independently managing deliverables</li></ul>
Preferred Qualifications<ul><li>
Experience in designing and building data engineering solutions in cloud environments (preferably GCP)</li><li>
Experience with Git, CI/CD pipeline, and other DevOps principles/best practices</li><li>
Experience with bash shell scripts, UNIX utilities &amp; UNIX Commands</li><li>
Ability to leverage multiple tools and programming languages to analyze and manipulate data sets from disparate data sources</li><li>
Knowledge of API development</li><li>
Experience with complex systems and solving challenging analytical problems</li><li>
Strong collaboration and communication skills within and across teams</li><li>
Knowledge of data visualization and reporting</li><li>
Experience with schema design and dimensional data modeling</li><li>
Google Professional Data Engineer Certification</li><li>
Knowledge of microservices and SOA</li><li>
Formal SAFe and/or agile experience. Previous healthcare experience and domain knowledge</li><li>
Experience designing, building, and maintaining data processing systems</li><li>
Experience architecting and building data warehouse and data lakes</li></ul>
Education<ul><li>
Bachelor&rsquo;s Degree or equivalent work experience in Computer Science, Information Systems, Data Engineering, Data Analytics, Machine Learning, or related field required</li><li>
Master&rsquo;s Degree preferred</li></ul>
Anticipated Weekly Hours
40
Time Type
Full time
Pay Range
The typical pay range for this role is:
$83,430.00 - $222,480.00
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. 
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in our comprehensive and competitive mix of pay and benefits &ndash; investing in the physical, emotional and financial wellness of our colleagues and their families to help them be the healthiest they can be. In addition to our competitive wages, our great benefits include:<ul><li>
Affordable medical plan options, a 401(k) plan (including matching company contributions), and an employee stock purchase plan.</li><li>
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching.</li><li>
Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.</li></ul>
For more information, visit https://jobs.cvshealth.com/us/en/benefits
We anticipate the application window for this opening will close on: 03/30/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.</div>

<div>Position Purpose:
The Sr Machine Learning Engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. Sr ML Engineers are expected to pair daily as they work through user stories and support products as they evolve. 
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering. 
Sr ML Engineers should be able to operate independently though will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices. 
Key Responsibilities:<ul><li>
70% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do &quot;destructive testing&quot; to ensure adequate resiliency in production; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
10% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This Position typically reports to Software Engineer Manager or Sr. Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
2 - 4 years of relevant work experience</li><li>
Experience to algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Experience to basic statistics and regression algorithms</li><li>
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc</li><li>
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc- Experience in a modern scripting language (preferably Python)</li><li>
Experience with GPU acceleration (i.e. CUDA and cuDNN)</li><li>
Experience in modern web application framework such as Node.js</li><li>
Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3</li><li>
Experience in writing SQL queries against a relational database</li><li>
Experience in version control systems (preferable Git)</li><li>
Experience in a Linux or Unix based environment</li><li>
Experience in a CI/CD toolchain</li><li>
Experience in REST and effective web service design</li><li>
Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li><li>
Familiarity with NoSQL databases</li><li>
Familiarity with cloud computing platform and associated automation patterns and machine learning services they provide</li><li>
Familiarity with defensive coding practices and patterns for high Availability</li><li>
Familiarity with A/B testing and effective REST design for scalable web services architecture</li><li>
Familiarity with advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
2</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul></div>

Senior Machine Learning Engineer (Remote)

Cortland

<div>
 
 Role Overview
 
 
 
 Cortland Asset Management , LLC has a full-time opening for Lead Data Engineer in Atlanta, GA 30326. Duties are to design the architecture of a data platform. Develop, customize and manage integration tools, databases, and analytical systems. Build data pipelines, test reliability and performance of the system. Responsible to manage data and meta-data and structure it appropriately in a database management system. Improve awareness and democratize data across organization by publishing data catalogs. Provide data access tools for advanced and business users to extract data, view data, and visualizations. Responsible for performance optimization at database layer and data ingestion frameworks. Build continuous integration and deployment models and automate release pipelines. Support deployment of machine learning models using the CI/CD pipelines. Work closely with infrastructure team to build a secure and reliable eco-system. Work with business teams to solve real business problems using data and provide needed insights. Bachelor&rsquo;s Degree or its foreign equivalent in Comp. Science, Engineering, Math, Stats., or related quantitative field. Plus 5 years&rsquo; experience in job offered or closely related technical position. Experience must include the following: 2 years with Azure Cloud Technologies (Data Factory, PowerShell, Data Lake and Data Lake Analytics); 5 years with Data Modeling and ETL tools, Business Intelligence platforms, API Integration, and Object-Oriented Programming (OOP) and utilizing modern technologies (Python, Git, Jenkins, Octopus Deploy, Tensorflow, Domo, ArcGIS, E/R Studio, RedGate DLM Automation and 1 year with Azure HDInsight + Spark, Azure Databricks, Azure Stream Analytics. Email resumes to: careers@cortland.com.
</div>

Lead Data Engineer - Atlanta, GA

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