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Remote Aws Machine Learning Jobs in New York (NOW HIRING)

Hang

Machine Learning Engineer

New York, NY · On-site +1

This person will implement and develop machine learning models to enhance our platform ... Experience with snowflake, Postgres, RDS, Redis and AWS. * Excellent problem-solving skills and ...

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

We are looking for an outstanding machine learning engineer to join our team! The role will provide ... Experience with cloud technologies (Google Cloud, AWS, Modal) * You are a self-starter who drives ...

Headspace

Staff Machine Learning Engineer

New York, NY · On-site +1

$179K - $224K/yr

Experience with AWS, including SageMaker, Lambda, S3, DynamoDB, IAM Location: This role is open to ... City, NY (remote), and Seattle, WA (remote). Candidates must permanently reside in the US ...

Headspace

Principal Machine Learning Engineer

New York, NY · On-site +1

$207K - $258K/yr

Experience with AWS, including SageMaker, Lambda, S3, DynamoDB, IAM Location: This role is open to ... City, NY (remote), and Seattle, WA (remote). Candidates must permanently reside in the US ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Canals

Machine Learning Engineer

New York, NY · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Lead Machine Learning Engineer

Manhattan, NY · On-site +1

$112K - $148K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

DailyPay

Senior Machine Learning Engineer

New York, NY · Remote

$190K - $250K/yr

Manage and optimize AWS infrastructure for machine learning workloads, balancing cost-effectiveness, security, and availability. * CI/CD Pipeline Development: Build and maintain robust CI/CD ...

Career Renew

Senior Machine Learning Engineer

New York, NY · Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... AWS, GCP, or Azure) Knowledge of handling large scale image data, data version controls, model ...

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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 New York? The most popular types of Aws Machine Learning jobs in New York are:
What are popular job titles related to Remote Aws Machine Learning jobs in New York? For Remote Aws Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Remote Aws Machine Learning jobs in New York look for? The top searched job categories for Remote Aws Machine Learning jobs in New York are:
What cities in New York are hiring for Remote Aws Machine Learning jobs? Cities in New York with the most Remote Aws Machine Learning job openings:
Remote Aws Machine Learning jobs near you
Infographic showing various Remote Aws Machine Learning job openings in New York as of July 2026, with employment types broken down into 71% Full Time, 12% Part Time, and 17% Contract. Highlights an 5% In-person, and 95% Remote job distribution.
Machine Learning Operations Engineer - Remote

Machine Learning Operations Engineer - Remote

NAVA Software Solutions

Jersey City, NJ • On-site, Remote

$76K - $102K/yr

Full-time

Re-posted 15 days ago

Job description

NAVA Software solutions is looking for a Machine Learning Operations Engineer
Details:
Machine Learning Operations (MLOps) Engineer - AWS (with LLM Focus)
Location: Remote work
Duration: 12 months
Responsibilities:
  • LLM-Optimized MLOps Infrastructure: Design and implement MLOps infrastructure on AWS tailored for LLMs, leveraging services like SageMaker, EC2 (with GPU instances), S3, ECS/EKS, Lambda, and more.
  • LLM Deployment Pipelines: Build and manage CI/CD pipelines specifically for LLM deployment, addressing unique challenges like model size, inference optimization, and versioning.
  • LLMOps Practices: Implement LLMOps best practices for monitoring model performance, drift detection, prompt management, and feedback loops for continuous improvement.
  • RESTful API Development: Design and develop RESTful APIs to expose LLM capabilities to other applications and services, ensuring scalability, security, and optimal performance.
  • Model Optimization: Apply techniques like quantization, distillation, and pruning to optimize LLM models for efficient inference on AWS infrastructure.
  • Monitoring and Observability: Establish comprehensive monitoring and alerting mechanisms to track LLM performance, latency, resource utilization, and potential biases.
  • Prompt Engineering and Management: Develop strategies for prompt engineering and management to enhance LLM outputs and ensure consistency and safety.
  • Collaboration: Work closely with data scientists, researchers, and software engineers to integrate LLM models into production systems effectively.
  • Cost Optimization: Continuously optimize LLMOps processes and infrastructure for cost-efficiency while maintaining high performance and reliability.

Qualifications:
  • Experience: 3+ years of experience in MLOps or a related field, with hands-on experience in deploying and managing LLMs.
  • AWS Expertise: Strong proficiency in AWS services relevant to MLOps and LLMs, including SageMaker, EC2 (with GPU instances), S3, ECS/EKS, Lambda, and API Gateway.
  • LLM Knowledge: Deep understanding of LLM architectures (e.g., Transformers), training techniques, and inference optimization strategies.
  • Programming Skills: Proficiency in Python and experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation), REST API frameworks (e.g., Flask, FastAPI), and LLM libraries (e.g., Hugging Face Transformers).
  • Monitoring: Familiarity with monitoring and logging tools for LLMs, such as Prometheus, Grafana, and CloudWatch.
  • Containerization: Experience with Docker and container orchestration (e.g., Kubernetes, ECS) for LLM deployment.
  • Problem Solving: Excellent problem-solving and troubleshooting skills in the context of LLMs and MLOps.
  • Communication: Strong communication and collaboration skills to effectively work with cross-functional teams
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About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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