Explore 2 python aws developer jobs from 2 hiring companies in Rockville, IN, US. Filter by remote, salary, experience, and company, then open any listing to apply.

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Python Aws Developer Jobs

Digital.ai

Group 1001

Hybrid

<div class="content-intro">About Digital.ai
Digital.ai is the only AI-powered software delivery platform purpose-built for the enterprise, enabling the world’s largest organizations to build, test, secure, and deliver high-quality software. By unifying AI-driven insights, automation, and security across the software development lifecycle, Digital.ai empowers enterprises to deliver innovation with confidence. Trusted by 5,000 global enterprises, Digital.ai is redefining how enterprises build better software in an AI-driven world. Additional information about Digital.ai can be found at&nbsp;<a href="https://digital.ai/">digital.ai</a>&nbsp;and on&nbsp;<a href="https://twitter.com/digitaldotai" target="_blank">Twitter</a>,&nbsp;<a href="https://www.linkedin.com/company/digitaldotai/" target="_blank">LinkedIn</a>,&nbsp;and&nbsp;<a href="https://www.youtube.com/@digital-ai7016" target="_blank">YouTube.</a></div>EMPLOYER:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Digital.ai
POSITION TITLE:&nbsp; CloudOps Engineer
LOCATION:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Lafayette, Indiana
DUTIES: Develop and manage the infrastructure for SaaS applications hosted within the Cloud; Create, deploy, and maintain the infrastructure used to host these applications; Manage and maintain the infrastructure as code in AWS using toolset terraform, ansible, puppet, etc. and monitor using tools such as Grafana Cloud, Nagios and AWS CloudWatch; Automate deployments using CI/CD pipelines using Jenkins/Github/etc.; Work directly with product development teams to design and implement cloud infrastructure needed for products; Manage the deployment of products into the Cloud; Provide on-call coverage during assigned shifts, responding to incidents that occur; Configure and manage complex build environments using Jenkins; Manage test automation hardware for mobile test suites; Implement virtual test environments using a variety of Linux image builds; Configure and support other development resources; and Administration of cloud systems (dev, test, production). The position permits some telecommuting within a reasonable commuting distance from Lafayette, Indiana.
REQUIREMENTS: &nbsp;Bachelor’s Degree in Computer Science or a closely related field plus two years of relevant experience. Experience must include 2 years of experience in Systems Engineering, DevOps or software development; 2 years of experience using build tools such as Jenkins, make, or ant; 2 years of experience automating build processes; and 2 years of experience working with a Tier one cloud provider, such as AWS, Azure or Google Cloud. All experience can be gained concurrently. In addition, the position requires knowledge of coding/scripting language such as Python or Bash.
SALARY: $106,609.64 per year.

CloupOps Engineer 

CloudOps Engineer

Bachelor's in CS or related field plus 2 years in DevOps/Systems Engineering; 2+ yrs with Jenkins/CI; 2+ yrs cloud (AWS/Azure/GCP); scripting in Python or Bash.

Group 1001 is a consumer-centric, technology-driven family of insurance companies on a mission to deliver outstanding value and operational performance by combining financial strength and stability with deep insurance expertise and a can-do culture. Group1001’s culture emphasizes the importance of collaboration, communication, core business focus, risk management, and striving for outcomes. This goal extends to how we hire and onboard our most valuable assets – our employees.<div><h2>Why This Role Matters:</h2></div>We&#39;re building AI&amp;ML-powered products that will transform how Group 1001 approaches pricing optimization, claims automation, and risk intelligence. To do this at scale, we need robust ML infrastructure—not just great models.As a Staff ML Engineer, you&#39;ll focus on the MLOps and infrastructure layer that makes ML production-ready: model serving, feature pipelines, experiment tracking, and CI/CD for ML. You&#39;ll help shape our ML platform architecture, working alongside Platform Engineering teams to ensure ML workloads run reliably on our modern stack: Snowflake, Dagster, Coalesce, Palantir and AWS SageMaker.This role is for engineers who are as passionate about infrastructure, deployment, and operationalizing ML as they are about the models themselves*Please note, this position requires an in-person interview.<div><h2>How You&#39;ll Contribute:</h2></div><ul><li>Partner with Data &amp; Platform Engineering to define how ML workloads integrate with our Snowflake-Dagster-Palantir ecosystem</li><li>Evaluate and recommend tooling for the ML stack—balancing build vs. buy decisions against our scale and compliance needs</li><li>Contribute to platform roadmap discussions, advocating for infrastructure investments that accelerate ML delivery</li><li>Establish CI/CD pipelines for ML: automated testing, model validation, staged deployments, and rollback capabilities using SageMaker Pipelines, Step Functions, or similar orchestration</li><li>Implement model monitoring and observability: drift detection, performance degradation alerts, and automated retraining triggers</li><li>Architect ML workloads on AWS: SageMaker (Training Jobs, Processing, Endpoints), EC2/EKS for custom serving, S3 for artifact storage, and IAM for secure access patterns</li><li>Optimize for cost and performance—right-sizing instances, spot instance strategies, auto-scaling endpoints, and efficient GPU utilization</li><li>Integrate ML infrastructure with our Dagster orchestration layer for end-to-end pipeline visibility</li><li>Mentor senior ML engineers and technical leads, developing the next generation of ML engineering leadership</li></ul><div><h2>What We&#39;re Looking For:</h2></div>Technical Skills:<ul><li>MLOps &amp; Model Serving: Hands-on experience with model serving frameworks (SageMaker Endpoints, Seldon Core, BentoML, Ray Serve, or TensorFlow Serving); building and operating inference infrastructure at scale</li><li>CI/CD for ML: Building ML pipelines with SageMaker Pipelines, Kubeflow, Airflow, or Dagster; automated model testing, validation gates, and deployment automation</li><li>AWS &amp; Cloud Infrastructure: Strong AWS experience—SageMaker, EKS/ECS, Lambda, Step Functions, S3, IAM; infrastructure-as-code (Terraform, CDK, CloudFormation)</li><li>Monitoring &amp; Observability: Model monitoring, drift detection, alerting; tools like Evidently, WhyLabs, SageMaker Model Monitor, or custom solutions</li><li>Core ML Fundamentals: Working knowledge of Python, ML frameworks (PyTorch, TensorFlow, scikit-learn), and model evaluation—enough to partner effectively with data scientists</li><li>Feature Engineering Infrastructure: Experience with feature stores (SageMaker Feature Store, Feast, Tecton, or similar); designing feature pipelines for both batch and real-time serving</li><li>Experiment Tracking &amp; Registry: MLflow, Weights &amp; Biases, SageMaker Experiments, or similar; establishing reproducibility and governance across ML projects</li><li>Nice to Have: Palantir Foundry, Kubernetes, Bedrock, cost optimization strategies for ML workloads</li></ul>Education:<ul><li>Bachelor&#39;s degree in Computer Science, Data Science, Engineering, or related field</li><li>Master&#39;s degree or equivalent experience preferred</li></ul>Experience:<ul><li>7-10 years in ML engineering, MLOps, or platform engineering with a focus on productionizing ML systems</li><li>Demonstrated experience building ML infrastructure that others build upon—serving layers, feature stores, or MLOps tooling</li><li>Track record of improving ML delivery velocity through infrastructure and automation</li><li>Proven ability to work cross-functionally with data scientists, platform engineers, and stakeholders</li><li>Experience mentoring and developing senior engineers and technical leaders</li><li>Strong executive presence with ability to influence stakeholders at all levels of the organization</li></ul>Preferred Qualifications:<ul><li>Experience in insurance or financial services with deep understanding of industry challenges</li><li>Recognized expertise through conference presentations, publications, or industry speaking engagements</li><li>Experience with enterprise-scale systems and complex technical environments</li><li>Proven ability to build consensus and drive alignment across multiple teams and stakeholders</li></ul>Competencies and Soft Skills:<ul><li>Executive presence with ability to influence senior leadership and drive organizational change</li><li>Strategic vision with ability to define long-term technical direction aligned with business goals</li><li>Strong leadership skills with proven ability to develop and mentor senior technical talent</li><li>Exceptional communication skills with ability to articulate technical strategy to executive audiences</li><li>Political acumen with ability to navigate complex organizational dynamics and build consensus</li></ul>Benefits Highlights:  Employees who meet benefit eligibility guidelines and work 30 hours or more weekly, have the ability to enroll in Group 1001’s benefits package. Employees (and their families) are eligible to participate in the Company’s comprehensive health, dental, and vision insurance plan options.  Employees are also eligible for Basic and Supplemental Life Insurance, Short and Long-Term Disability. All employees (regardless of hours worked) have immediate access to the Company’s Employee Assistance Program and wellness programs—no enrollment is required.  Employees may also participate in the Company’s 401K plan, with matching contributions by the Company.  Group 1001, and its affiliated companies, is strongly committed to providing a supportive work environment where employee differences are valued. Diversity is an essential ingredient in making Group 1001 a welcoming place to work and is fundamental in building a high-performance team. Diversity embodies all the differences that make us unique individuals.  All employees share the responsibility for maintaining a workplace culture of dignity, respect, understanding and appreciation of individual and group differences.

Staff ML Engineer

7-10 years in ML engineering/MLOps or platform engineering; production ML infrastructure; AWS SageMaker; Snowflake-Dagster-Palantir ecosystem; CI/CD for ML.

Python Aws Developer Jobs in Rockville, IN, US | HiringCafe: every job on earth

Python Aws Developer Jobs in Rockville, IN, US

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