Machine Learning Engineer | MLOps & Scalable Systems
Are you a senior-level Machine Learning Engineer ready to make a big impact at scale? We're looking for a highly skilled ML Engineer to lead the design and deployment of production-grade machinelearning systems in a complex enterprise environment. You’ll own the full MLOps lifecycle—from prototyping tomonitoring—and architect solutions that power intelligent, real-time decision-making across critical businessfunctions.
This is a high-visibility role where you’ll collaborate with cross-functional teams, influence architecture, and helpdefine best practices that shape the future of ML at scale.
What You’ll Do:
- Lead MLOps Initiatives: Design, build, deploy, and monitor end-to-end ML solutions that are scalable,reliable, and secure.
- Architect for Scale & Speed: Build applications optimized for low latency on high-volume data pipelinesand streaming environments.
- Advise & Innovate: Act as a thought partner to data scientists and engineering leaders, bringing deepdomain expertise in ML model design and infrastructure.
- Collaborate Cross-Functionally: Work with enterprise architects, product teams, and data scientists todeliver real-world business value.
- Own Quality & Governance: Establish and maintain best practices for ML lifecycle management, includingCI/CD, monitoring, testing, and documentation.
You’ll Be a Great Fit If You Have:
- Held a Machine Learning Engineer or MLOps role in a large-scale enterprise environment.
- Deep experience with modern ML models, cloud-native data platforms, and orchestration tools (e.g.,Kubeflow, SageMaker, MLflow).
- Proven ability todesign scalable ML architecturesfor streaming and batch use cases.
- A mindset formentorship and technical leadership, with the ability to guide teams on best practices inproduction ML.
Machine Learning Engineer | Information Technology
- BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field
- PLUS minimum four(4) years directly related data analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role
- OR advanced degree and two (2) years directly related experience. Possesses a combination of strong analytical and problem-solving skills and programming knowledge, or an equivalent combination of education and experience with demonstrated comparable knowledge and abilities.
Machine Learning Engineer, Senior | Information Technology
- BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field
- PLUS minimum six (6) years directly related data analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role
- OR advanced degree and four (4) years directly related experience. Possesses a combination of strong analytical and problem-solving skills and programming knowledge, or an equivalent combination of education and experience with demonstrated comparable knowledge and abilities.
Preferred Special Skills, Knowledge or Qualifications:
- Masters or Doctorate degrees in related fields.
- Knowledge/experience in utility industry and business functions.
- Certification in Data Science and/or predictive analytics
- A high level of proficiency in commonly used programming languages and tools like R Programming, Python and SQL.
- Strong communication, presentation and writing skills.
- Must be able to lead teams in evaluations and implementation of solutions.
- Must be able to work with key internal and external stakeholders and all levels of management.
5-10 years96
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Job Description
Download ResumeMachine Learning Engineer | MLOps & Scalable Systems
Are you a senior-level Machine Learning Engineer ready to make a big impact at scale? We're looking for a highly skilled ML Engineer to lead the design and deployment of production-grade machinelearning systems in a complex enterprise environment. You’ll own the full MLOps lifecycle—from prototyping tomonitoring—and architect solutions that power intelligent, real-time decision-making across critical businessfunctions.
This is a high-visibility role where you’ll collaborate with cross-functional teams, influence architecture, and helpdefine best practices that shape the future of ML at scale.
What You’ll Do:
- Lead MLOps Initiatives: Design, build, deploy, and monitor end-to-end ML solutions that are scalable,reliable, and secure.
- Architect for Scale & Speed: Build applications optimized for low latency on high-volume data pipelinesand streaming environments.
- Advise & Innovate: Act as a thought partner to data scientists and engineering leaders, bringing deepdomain expertise in ML model design and infrastructure.
- Collaborate Cross-Functionally: Work with enterprise architects, product teams, and data scientists todeliver real-world business value.
- Own Quality & Governance: Establish and maintain best practices for ML lifecycle management, includingCI/CD, monitoring, testing, and documentation.
You’ll Be a Great Fit If You Have:
- Held a Machine Learning Engineer or MLOps role in a large-scale enterprise environment.
- Deep experience with modern ML models, cloud-native data platforms, and orchestration tools (e.g.,Kubeflow, SageMaker, MLflow).
- Proven ability todesign scalable ML architecturesfor streaming and batch use cases.
- A mindset formentorship and technical leadership, with the ability to guide teams on best practices inproduction ML.
Machine Learning Engineer | Information Technology
- BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field
- PLUS minimum four(4) years directly related data analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role
- OR advanced degree and two (2) years directly related experience. Possesses a combination of strong analytical and problem-solving skills and programming knowledge, or an equivalent combination of education and experience with demonstrated comparable knowledge and abilities.
Machine Learning Engineer, Senior | Information Technology
- BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field
- PLUS minimum six (6) years directly related data analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role
- OR advanced degree and four (4) years directly related experience. Possesses a combination of strong analytical and problem-solving skills and programming knowledge, or an equivalent combination of education and experience with demonstrated comparable knowledge and abilities.
Preferred Special Skills, Knowledge or Qualifications:
- Masters or Doctorate degrees in related fields.
- Knowledge/experience in utility industry and business functions.
- Certification in Data Science and/or predictive analytics
- A high level of proficiency in commonly used programming languages and tools like R Programming, Python and SQL.
- Strong communication, presentation and writing skills.
- Must be able to lead teams in evaluations and implementation of solutions.
- Must be able to work with key internal and external stakeholders and all levels of management.