Senior Machine Learning Engineer - Atlanta, United States - 3i People

Description

Bachelor's or Master's degree in Computer Science, Data Science, or a related field
Proven experience in ML Ops or a similar role, with a deep understanding of machine learning and software engineering principles
Strong knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, Azure, GCP)
Experience with Software as a Service platforms to include SAS, , and AWS Sagemaker
Proficiency in programming languages such as Python, and experience with automation and scripting
Familiarity with machine learning frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn)
Excellent problem-solving skills and the ability to troubleshoot complex issues in a production environment
Strong communication and collaboration skills
Opportunity to work on cutting-edge projects in the AI and ML space
Responsibilities

As the ML Ops Lead, you will play a critical role in bridging the gap between data science and production.

You will be responsible for implementing and managing the infrastructure, processes, and tools necessary to deploy, monitor, and maintain machine learning models in a production environment.

You will work closely with data scientists, engineers, and other stakeholders to ensure the seamless integration of machine learning solutions into our products and services

ML Model Deployment:
Lead the deployment of machine learning models into production environments, ensuring they are scalable, reliable, and maintainable

Infrastructure Management:
Collaborate with the IT and DevOps teams to provision and manage the necessary infrastructure, including cloud resources, containers, and data pipelines, to support machine learning workloads

Automation:
Develop and maintain automation scripts and tools for model deployment, monitoring, and retraining, with a focus on efficiency and reproducibility

Model Monitoring:
Implement robust monitoring and alerting systems to track model performance, data drift, and anomalies, and take proactive steps to address issues as they arise

Security and Compliance:
Ensure that machine learning models and data pipelines adhere to security and compliance standards, and work closely with security teams to address any vulnerabilities or risks

Collaboration:
Collaborate with data scientists and engineers to understand model requirements, and work together to optimize models for deployment

Documentation:
Maintain clear and comprehensive documentation of ML Ops processes, procedures, and configurations

Continuous Improvement:
Stay up-to-date with industry best practices and emerging technologies in ML Ops, and proactively identify opportunities to enhance the ML Ops workflow

Team Leadership:
Mentor and guide junior ML Ops engineers and contribute to their skill development
Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, or a related field
Proven experience in ML Ops or a similar role, with a deep understanding of machine learning and software engineering principles
Strong knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, Azure, GCP)
Experience with Software as a Service platforms to include SAS, , and AWS Sagemaker
Proficiency in programming languages such as Python, and experience with automation and scripting
Familiarity with machine learning frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn)
Excellent problem-solving skills and the ability to troubleshoot complex issues in a production environment
Strong communication and collaboration skills
Opportunity to work on cutting-edge projects in the AI and ML space
Responsibilities

As the ML Ops Lead, you will play a critical role in bridging the gap between data science and production.

You will be responsible for implementing and managing the infrastructure, processes, and tools necessary to deploy, monitor, and maintain machine learning models in a production environment.

You will work closely with data scientists, engineers, and other stakeholders to ensure the seamless integration of machine learning solutions into our products and services

ML Model Deployment:
Lead the deployment of machine learning models into production environments, ensuring they are scalable, reliable, and maintainable

Infrastructure Management:
Collaborate with the IT and DevOps teams to provision and manage the necessary infrastructure, including cloud resources, containers, and data pipelines, to support machine learning workloads

Automation:
Develop and maintain automation scripts and tools for model deployment, monitoring, and retraining, with a focus on efficiency and reproducibility

Model Monitoring:
Implement robust monitoring and alerting systems to track model performance, data drift, and anomalies, and take proactive steps to address issues as they arise

Security and Compliance:
Ensure that machine learning models and data pipelines adhere to security and compliance standards, and work closely with security teams to address any vulnerabilities or risks

Collaboration:
Collaborate with data scientists and engineers to understand model requirements, and work together to optimize models for deployment

Documentation:
Maintain clear and comprehensive documentation of ML Ops processes, procedures, and configurations

Continuous Improvement:
Stay up-to-date with industry best practices and emerging technologies in ML Ops, and proactively identify opportunities to enhance the ML Ops workflow

Team Leadership:
Mentor and guide junior ML Ops engineers and contribute to their skill development
Transforming Careers, One Opportunity at a Time

At 3i People, we're more than recruiters; we're career accelerators. Partnered with cutting-edge tech firms and innovative companies, we connect top-tier talent with their dream jobs. Our mission is to open doors for professionals like you to thriving workplaces where you can leave your mark...

We have the below position open with our direct direct. If interested, please email me your updated resume to to proceed further. Else, if you'd like to forward this opportunity to a colleague or friend, I'd appreciate that very much

Machine Learning OPS Lead

Job Title:
ML Ops Lead


Department:
Operations


Location:
Atlanta GA


Reports To:
Sr. Manager of Operations


Position Overview:

As the ML Ops Lead, you will play a critical role in bridging the gap between data science and production.

You will be responsible for implementing and managing the infrastructure, processes, and tools necessary to deploy, monitor, and maintain machine learning models in a production environment.

You will work closely with data scientists, engineers, and other stakeholders to ensure the seamless integration of machine learning solutions into our products and services.

Key Responsibilities:

ML Model Deployment:
Lead the deployment of machine learning models into production environments, ensuring they are scalable, reliable, and maintainable.


Infrastructure Management:

Collaborate with the IT and DevOps teams to provision and manage the necessary infrastructure, including cloud resources, containers, and data pipelines, to support machine learning workloads.

Automation:

Develop and maintain automation scripts and tools for model deployment, monitoring, and retraining, with a focus on efficiency and reproducibility.

Model Monitoring:

Implement robust monitoring and alerting systems to track model performance, data drift, and anomalies, and take proactive steps to address issues as they arise.

Security and Compliance:

Ensure that machine learning models and data pipelines adhere to security and compliance standards, and work closely with security teams to address any vulnerabilities or risks.

Collaboration:
Collaborate with data scientists and engineers to understand model requirements, and work together to optimize models for deployment.


Documentation:
Maintain clear and comprehensive documentation of ML Ops processes, procedures, and configurations.


Continuous Improvement:

Stay up-to-date with industry best practices and emerging technologies in ML Ops, and proactively identify opportunities to enhance the ML Ops workflow.

Team Leadership:
Mentor and guide junior ML Ops engineers and contribute to their skill development.


Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Proven experience in ML Ops or a similar role, with a deep understanding of machine learning and software engineering principles.
• Strong knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, Azure, GCP).
• Experience with Software as a Service platforms to include SAS, , and AWS Sagemaker
• Proficiency in programming languages such as Python, and experience with automation and scripting.
• Familiarity with machine learning frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn).
• Excellent problem-solving skills and the ability to troubleshoot complex issues in a production environment.
• Strong communication and collaboration skills.
• Experience with DevOps practices and tools is a plus.
• Opportunity to work on cutting-edge projects in the AI and ML space.

If you are passionate about machine learning and have a strong background in deploying and managing ML models in production, we encourage you to apply for the ML Ops Lead position at [Insert Company Name].

Join us in shaping the future of AI-driven solutions and making an impact in our industry

Company information

3i People has been providing staffing solutions in IT and professional services for over 20+ years and has established a reputation for delivering top-quality talent to meet the unique requirements of their clients.

We have developed a deep understanding of the industry and the evolving trends, which enables us to provide our clients with the most relevant talent.

Additionally, our vast experience allows us to offer a personalized approach to staffing, catering to each client's specific needs.

Overall, 3i People's extensive experience and expertise in the staffing industry make us a reliable and trusted partner for companies looking for top talent.

Our commitment to delivering high-quality services and using innovative technologies, such as Leap Tiger, further set us apart from our competitors.

With our personalized approach and dedication to excellence, 3i People is well-equipped to help clients succeed in the ever-changing business environment.

One key factor that sets 3i People apart is using a proprietary AI-based application tracking system called Leap Tiger. This system has been designed to streamline the recruitment process and make it more efficient. With Leap Tiger, 3i People can manage job postings, track applicants, and review resumes all in one place.

Furthermore, Leap Tiger enables 3i People to quickly and easily identify the most qualified candidates by searching for specific keywords and phrases related to the job description.

The system also enables recruiters to track candidate communications and interview feedback, ensuring a seamless and effective recruitment process from start to finish.

In addition to using cutting-edge technology, 3i People also takes a personalized approach to staffing. We work closely with each client to understand their unique needs and tailor their services accordingly. This means that clients can expect to receive a customized and personalized experience tailored to their specific requirements.
Information Technology and Services, Management Consulting, Human Resources, Staffing and Recruiting, Outsourcing/Offshoring
Privately Held

Company Specialties:
Staff Augmentation, Software / Mobile Development, Project Management, Business Intelligence, and Cloud

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