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Startup Machine Learning Remote Jobs in New Jersey

Adidev Technologies

AI/ML

Hoboken, NJ · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ...

Gnostech

Software Engineer (US-Remote)

Marlton, NJ · On-site +1

Overview Location * US-Remote or Marlton, NJ area Job Title * Software Engineer Salary ... Build and integrate AI-enabled capabilities into applications, including machine learning models ...

Dlapiper

Data Scientist

Short Hills, NJ · On-site +1

A specialization in machine-learning, artificial intelligence, cognitive science or data science is ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Databricks

$105K - $145K/yr

This role can be remote. The impact you will have: * Develop cutting-edge GenAI solutions ... Experience building production-grade machine learning deployments on AWS, Azure, or GCP * Graduate ...

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Startup Machine Learning Remote information

What is a startup machine learning engineer remote?

Remote startup machine learning jobs involve working for early-stage companies or startups to design, develop, and implement machine learning models and solutions, all while working from a remote location. These roles typically require strong programming skills, experience with data analysis, and familiarity with machine learning frameworks. Startups often offer dynamic environments where employees can work on diverse projects and contribute directly to the product's growth. Remote positions provide flexibility in work location and hours, but also require self-motivation and excellent communication skills to collaborate with distributed teams.

What skills and qualifications are needed to thrive as a startup machine learning engineer remote?

To thrive as a Startup Machine Learning Engineer remotely, you need a solid background in computer science, statistics, and machine learning algorithms, typically supported by a relevant degree or equivalent experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms (AWS, GCP, or Azure), and version control systems like Git is essential. Strong self-motivation, communication skills, and the ability to collaborate effectively across time zones help set outstanding candidates apart. These skills and qualities are crucial for delivering impactful ML solutions independently while contributing to fast-paced, distributed startup teams.

What are some unique challenges faced by startup machine learning engineers working remotely?

Machine learning professionals at startups often encounter fast-paced environments where priorities can shift quickly, and working remotely adds another layer of complexity. Collaboration with cross-functional teams, such as engineers and product managers, may require proactive communication to ensure alignment and clarity on project goals. Additionally, limited resources and data infrastructure at startups may mean you'll need to wear multiple hats and help shape processes from the ground up. However, this environment offers high autonomy, opportunities to have a direct impact, and rapid career growth potential as the startup scales.

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The top searched job categories for Startup Machine Learning Remote jobs in New Jersey are:

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Startup Machine Learning Remote jobs near you

Machine Learning Operations Engineer - Remote

NAVA Software Solutions

Jersey City, NJ • On-site, Remote

$76K - $102K/yr

Full-time

Re-posted 21 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

Social media

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