Machine Learning Engineer
Listed on 2026-10-03
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IT/Tech
Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Perfict Global is a leading IT consulting services provider focused on providing innovative and successful business workforce solutions to Fortune 500 companies. Our trained and experienced professionals constantly strive to bring together the best technologies available to manage client's complex business and technology, participate in implementation activities and collaborate in new ways to meet client needs.
We provide excellent benefits such as Medical, Dental, Vision ++ a fun company to work!!!
Job description POSITION SUMMARYCCS transforms chronic care management by combining equipment and products with comprehensive education, monitoring, and coaching to improve care outcomes and reduce acute episodes. With this collaborative care approach, we are redefining patient care. We are seeking a passionate Azure AI/Client Ops engineer to create data platform and pipeline to enable advanced analytics.
AI/MLOPS Engineers are the crafters of automation, turning data-driven models into practical applications. They take the prototypes developed by Data Scientists and fine-tune them for scalability, efficiency, and real- world deployment. Their expertise in machine learning frameworks and software engineering ensures that the predictive power of models seamlessly integrates into everyday operations.
ESSENTIAL DUTIES- Utilize Azure technologies like Azure Cognitive Technologies, Azure Machine Learning, and Azure Bot Services to design, create, and deploy AI/Client based applications.
- Include AI components into data workflows, engage with data scientists and data engineers.
- Utilize Azure AI services to implement natural language processing (NLP) create and implement machine learning models and algorithms.
- Automate the deployment and monitoring of AI models, collaborate with Dev Ops teams.
- Use AI to automate processes such as sentiment analysis, image identification, recommendation systems, and chatbots.
- Implementing machine learning pipelines and workflows
- Deploying and scaling Client models in production environments
- Automating CI/CD pipelines to account for data, code, and model changes
- Monitoring model performance and applying updates as needed
- Ensuring the security and compliance of machine learning systems
- Collaborating with data scientists to optimize models and improve performance
- Bachelor's Degree, (BA/BS) in Information Systems from a four-year college or university and 5 or more years of development experience required or equivalent combination or education and experience
- Travel up to 25%
- Total of 3-6 years of experience in managing machine learning projects end-to-end, with the last 18 months focused on MLOps
- Strong programming skills, preferably in languages like Python, Java, or Scala
- Proficiency in machine learning libraries and frameworks, such as Tensor Flow, PyTorch, or scikit-learn
- Experience with containerization technologies, like Docker and Kubernetes
- Familiarity with Client model deployment tools, such as MLflow or Kubeflow
- Working experience in Azure cloud platform
- Automation of machine learning model deployment
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to use sit, talk, hear; hands/fingers, handle, or feel;
reach with hands and arms. The employee frequently is required to stand and walk. The employee is occasionally required to stoop, kneel, or crouch. The employee must frequently lift and/or move up to twenty five pounds and occasionally lift and/or move up to fifty pounds. Vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus.
Moderate noise level similar to a typical office environment with computers, printers, and work activity.
EMPLOYEE ACKNOWLEDGMENTI acknowledge by my signature that I have read and understand the duties and responsibilities, physical demands, and work environment of the position and all other standards expected of me. I understand this job description in no way states or implies that these are the only duties to be performed by me in this position.
Nothing in this job description restricts the right of an authorized person to assign…
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