Summary : • Machine Learning Ops Engineer to build & support scalable, highly available and robust Machine Learning (ML) /Deep Learning (DL) platform using ML/DL frameworks, High-Performance ...
Summary : • Machine Learning Ops Engineer to build & support scalable, highly available and robust Machine Learning (ML) /Deep Learning (DL) platform using ML/DL frameworks, High-Performance ...
Looking for a Machine Learning Engineer with strong python, scala, AWS, Kubernetes & machine learning frameworks. * 80% of model Engineering work & 20% of operations work * Email arbitration with ...
Looking for a Machine Learning Engineer with strong python, scala, AWS, Kubernetes & machine learning frameworks. * 80% of model Engineering work & 20% of operations work * Email arbitration with ...
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Manhattan, NY · On-site +1
$180K - $280K/yr
Machine Learning Engineer Legal work is buried in unstructured documents, repetitive workflows, and data that no existing system handles well -- and we're building the AI to fix it. As a Machine ...
Machine Learning Engineer
Manhattan, NY · On-site +1
$180K - $280K/yr
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Manhattan, NY · Remote
$58.25 - $79.75/hr
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Machine Learning Engineer (GCP)
Manhattan, NY · Remote
$58.25 - $79.75/hr
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Manhattan, NY · Remote
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Manhattan, NY · Remote
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As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and ...
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$90K - $254K/yr
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New York, NY · Hybrid
$90K - $254K/yr
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New York, NY · On-site +1
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New York, NY · On-site +1
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New York, NY · On-site
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New York, NY · On-site
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New York, NY · On-site
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New York, NY · On-site
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New York, NY · On-site +1
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Lead Machine Learning Engineer
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$112K - $147K/yr
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Lead Machine Learning Engineer
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Lead Machine Learning Engineer
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Graduate Machine Learning Engineer information
See New York salary details
$34.5K - $50.6K
1% of jobs
$50.6K - $66.7K
1% of jobs
$66.7K - $82.8K
5% of jobs
$82.8K - $98.9K
6% of jobs
$112.2K is the 25th percentile. Wages below this are outliers.
$98.9K - $115K
14% of jobs
$115K - $131.1K
14% of jobs
The median wage is $139.2K / yr.
$131.1K - $147.2K
18% of jobs
$147.2K - $163.4K
14% of jobs
$166.7K is the 75th percentile. Wages above this are outliers.
$163.4K - $179.5K
12% of jobs
$179.5K - $195.6K
11% of jobs
$195.6K - $211.7K
5% of jobs
$34.5K
$140.9K
$211.7K
How much do graduate machine learning engineer jobs pay per year?
What does a Graduate Machine Learning Engineer do?
What are the key skills and qualifications needed to thrive as a Graduate Machine Learning Engineer, and why are they important?
What are some common challenges faced by Graduate Machine Learning Engineers during their first year, and how can they overcome them?
What is the difference between Graduate Machine Learning Engineer vs Data Scientist?
| Aspect | Graduate Machine Learning Engineer | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or Master's in CS, Data Science, or related field; some internships | Bachelor's or Master's in Statistics, Data Science, or related field; often with experience |
| Work Environment | Developing ML models, coding, testing algorithms | Analyzing data, creating visualizations, deriving insights |
| Employer & Industry Usage | Tech companies, startups, research labs | Finance, healthcare, tech, consulting firms |
While both roles involve working with data and algorithms, Graduate Machine Learning Engineers focus on developing and deploying machine learning models, often requiring coding and technical skills. Data Scientists analyze data to extract insights and inform decisions. The roles overlap in skills but differ in primary responsibilities and focus areas.
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Job description
• Machine Learning Ops Engineer to build & support scalable, highly available and robust Machine Learning (ML) /Deep Learning (DL) platform using ML/DL frameworks, High-Performance Computing (HPC) machines, Data Science tools, products & services in cloud and on-premises for client's data & analytics organization.
• Role will expose you to cutting edge technologies related to ML/DL and the ideal candidate will be driven, focused and enthusiastic about learning new technologies and implement them.
Responsibilities:
• Build, install, configure, manage, and scale state-of-the-art machine learning platform in cloud (Azure preferred) & on-premises powering client's Data & Analytics products and solutions.
• Work with data scientists, architects, DevOps engineers, and vendors to implement scalable ML/DL solutions in cloud and on-premises to solve complex problems.
• Creating & maintaining ML/DL pipelines and overall ML/DL workflow orchestration including but not limited to data collection, prep, transform, analyze, experiment, train, validate, serve, monitor, etc.
• Implement ML/DL solutions addressing performance, scalability, and the governance/ traceability of machine learning models
• Iterate quickly through latest technologies, products, frameworks, and R&D on latest information related to ML/DL frameworks, tools & services.
Qualifications:
• 4+ years' experience delivering DevOps and MLOps in a Production/Enterprise setting
• Bachelor's degree required; Masters preferred in Computer Science or Data Science
• Excellent written and oral communication and presentation skills.
• Experienced in a technical role involving platform and infrastructure operation.
• System administration experience of Unix or Linux systems.
• Container-based deployment experience using Docker and Kubernetes.
• Proficient with the machine learning modelling lifecycle and comfortable addressing both functional and technical aspects of model delivery
• Experience with managing, deployment of large distributed systems like Spark, DASK & H20 and heterogenous platform components.
• Experienced with programming languages like Python or R and comfortable in understanding statistical foundations of most used ML algorithms.
• Experienced with Machine Learning frameworks: Sci-kit, Keras, Theano, TensorFlow, Spark Mllib, etc.
• Preferred hand-on experience IBM Watson Machine Learning systems or related preferred
• Preferred hands-on experience with HPC - Nvidia, CUDA
• Preferred experience with configuration Management tools like Ansible, puppet
• Preferred experience in monitoring and performance analysis of Machine Learning platforms using tools like Grafana and Zabbix.
About Exaways
Sourced by ZipRecruiter
Company size
11 - 50 Employees
Headquarters location
Santa Clara, CA, US
Year founded
2015