Hiring - MlOps Lead Engineer - Remote US

Job Role: MlOps Lead Engineer

Duration:  6 -12 + months & Need 

Location: 100% Remote out of EST

Interview process: Phone or Skype

Start Date: within 2 weeks or ASAP

Top Skills' Details

1. 3+ years of experience operationalizing AI/ML models within an Azure environment with 10 year of total engineering experience

2. Strong Python and Docker/Kubernetes experience

3. 2+ Experience with Azure AI/ML services

ML Ops engineer to create data platform and pipeline to enable advanced analytics.

ML OPS 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/ML 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 DevOps 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 ML 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

POSITION REQUIREMENTS & COMPETENCIES:

• 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 ML Ops

• Strong programming skills, preferably in languages like Python, Java, or Scala

• Proficiency in machine learning libraries and frameworks, such as TensorFlow, PyTorch, or scikit-learn

• Experience with containerization technologies, like Docker and Kubernetes

• Familiarity with ML model deployment tools, such as MLflow or Kubeflow

• Working experience in Azure cloud platform