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Remote Aws Machine Learning Jobs in Georgia (NOW HIRING)

Motorola

Senior DevOps Engineer (US REMOTE)

Atlanta, GA · Remote

$140K - $170K/yr

Experience designing and deploying solutions to cloud environments (AWS) * Experience with IaC ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

Omnissa

Senior Data Scientist

Atlanta, GA · On-site +1

$146K - $304K/yr

Work with engineers to design and implement scalable machine learning pipelines, covering all ... Familiarity with cloud platforms and tools such as AWS, Azure, of Google Cloud for development and ...

Deckers

... and machine learning enablement * Promote architectural patterns that enable resilience ... AWS Certified Solutions Architect Professional or equivalent certifications are highly preferred ...

Elevance Health

Senior AI Solutions Engineer

Atlanta, GA · On-site +1

$53.25 - $68.50/hr

You will design, build, and deploy machine learning and LLM-based systems, taking models from ... Experience with cloud-based ML platforms and scalable architectures (AWS Bedrock, or equivalent AI ...

Elevance Health

Senior AI Solutions Engineer

Atlanta, GA · On-site +1

$53.25 - $68.50/hr

You will design, build, and deploy machine learning and LLM-based systems, taking models from ... Experience with cloud-based ML platforms and scalable architectures (AWS Bedrock, or equivalent AI ...

Slip Robotics

Robotics Perception Engineer

Atlanta, GA · On-site +1

Familiarity with machine learning frameworks (PyTorch, TensorFlow) for perception tasks * Track ... Remote team members are expected to have reliable high-speed internet access and a dedicated ...

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Remote Aws Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote AWS Machine Learning Engineer, and why are they important?

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What are remote AWS Machine Learning jobs?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

What is the difference between Remote Aws Machine Learning vs Remote Data Scientist?

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

What are some common challenges faced by remote AWS Machine Learning engineers, and how can they be addressed?

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.
What are the most commonly searched types of Aws Machine Learning jobs in Georgia? The most popular types of Aws Machine Learning jobs in Georgia are:
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Remote Aws Machine Learning jobs near you
Principal Decision Scientist, Applied Optimization and Simulation 2026 - US, UK

Principal Decision Scientist, Applied Optimization and Simulation 2026 - US, UK

Aimpoint Digital

Atlanta, GA • On-site, Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Principal Decision Scientist, Applied Optimization and Simulation 2026 - US

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision science, data engineering and infrastructure. This position is within our Decision Science practice which focuses on delivering solutions via optimization, simulation techniques, machine learning, and statistical modelling.

What you will do

As a part of Aimpoint Digital, you will focus on enabling clients to get the most out of their data. You will work with all levels of the client organization to build value driving solutions that extract insights and then train them on how to manage and maintain these solutions. Typical solutions will utilize machine learning, artificial intelligence, statistical analysis, automation, optimization, and/or data visualizations. A Principal Decision Scientist will define high-level business objectives directly with clients, then develop and execute the project plan to meet those objectives. You will proactively research and apply knowledge within the data science space to deliver best-in‑class solutions. You will lead both small and large teams over the entire data science lifecycle – from problem definition to model automation and deployment. As a Principal, you will be expected to provide technical leadership to guide development work across teams while also owning and delivering specific technical components yourself. A Principal Decision Scientist will also manage all aspects of client relationships and create value‑driving initiatives for the company.

Who we are looking for

We are looking for collaborative individuals who want to drive value, work in a fast‑paced environment, and solve real business problems. You are a coder who writes efficient and optimized code. You are a problem‑solver who can deliver simple, elegant solutions as well as cutting‑edge solutions that regardless of complexity, your clients can understand, implement, and maintain. You genuinely think about the end‑to‑end solution pipeline as you generate robust solutions. You are both a teacher and a student as we enable our clients, upskill our teammates, and learn from one another. You want to drive impact for your clients and do so through thoughtfulness, prioritization, and seeing a solution through from brainstorming to deployment.

  • MS/PhD in Operations Research, Industrial Engineering, Computer Science, Mathematics, Engineering, or other STEM‑related field
  • Strong theoretical knowledge of optimization techniques, including linear programming and integer programming and/or dynamic programming and graph theory
  • Proficiency in a programming language such as Python, and/or proficiency in an optimization platform, AIMMS/AMPL/GAMS/Pyomo
  • Practical experience with open‑source solvers and commercial solvers, such as Gurobi, CPLEX or XPRESS
  • Experienced in simulation techniques and tools such as Arena, Simio, Anylogic, JaamSim or Simpy
  • Familiar with a broad spectrum of advanced data science techniques, from cutting edge deep learning to time series and natural language processing
  • Experience delivering end‑to‑end data science projects, starting with project plan, through data modelling & data integrity checks to delivering value with explainable results
  • Strong analytical and problem‑solving skills
  • 5+ years of practical data science experience
  • 5+ years of consulting experience (preferred)
  • Self‑starter with excellent communication skills, able to work independently and collaboratively, and lead projects, initiatives, and/or people
  • Familiar with data visualization platforms such as PowerBI, Tableau or Sigma
  • Knowledge of any of the following tools is a plus: Databricks, Snowflake, Dataiku, AWS, Sagemaker
  • Oil and gas industry experience is a plus

We are actively seeking candidates for full‑time, remote work within the US. Atlanta‑based applicants will have the opportunity to work in our headquarters in Sandy Springs, GA.

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