- Collaboratewith crossfunctional teams to understand machine learning modelrequirements and deploy scalable solutions in productionenvironments.
- Develop and maintainautomation pipelines for model training testing deployment andmonitoring.
- Implement continuousintegration and continuous deployment (CI/CD) processes tostreamline model deployment andupdates.
- Optimize machine learninginfrastructure for performance scalability andcosteffectiveness.
- Design andimplement monitoring and alerting systems to track modelperformance data quality and systemhealth.
- Ensure data integritysecurity and compliance with regulatory requirements (e.g. GDPRHIPAA) throughout the machine learninglifecycle.
- Troubleshoot issuesrelated to model deployment infrastructure and datapipelines.
- Stay updated on emergingtechnologies and best practices in MLOps and contribute to theevolution of the MLOps framework within theorganization.
- Collaborate withDevOps teams to integrate machine learning workflows into existingCI/CD pipelines.
- Document processesworkflows and configurations to facilitate knowledge sharing andonboarding of new teammembers.
- Bachelorsor Masters degree in Computer Science Engineering Mathematics orrelated field.
- Proven experience (4years) in deploying and managing machine learning models inproduction environments.
- Strongprogramming skills in languages such as Python Java orScala.
- Experience with machinelearning frameworks and libraries (e.g. TensorFlow PyTorchscikitlearn).
- Proficiency incontainerization technologies such as Docker and orchestrationtools like Kubernetes.
- Solidunderstanding of cloud computing platforms (e.g. AWS Azure GoogleCloud) and experience with cloudbased MLservices.
- Familiarity with versioncontrol systems (e.g. Git) and collaboration tools (e.g. JiraConfluence).
- Knowledge of softwaredevelopment methodologies and best practices (e.g. AgileDevOps).
- Excellent problemsolvingand communication skills.
- Ability towork effectively in a fastpaced dynamic environment and collaboratewith crossfunctionalteams.
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ML Ops Engineer - hyderabad, India - DATAECONOMY
Description
As anMLOps Engineer you will be responsible for bridging the gap betweendata science and operations. You will collaborate closely with datascientists machine learning engineers and software developers todeploy manage and monitor machine learning models in productionenvironments. Your role will involve implementing automationpipelines ensuring scalability reliability and performance ofmachine learning systems and optimizing workflows for efficiency.Additionally you will play a key role in maintaining data integritysecurity and compliance throughout the machine learninglifecycle.
Responsibilities:
Qualifications:
Qualifications: Min 7+yrs of experience Proven experience as aTechnical Project Manager in a technology-driven environment.Strong technical background and understanding of softwaredevelopment life cycle (SDLC) or relevant technical domains.Excellent communication and interpersonal skills. ProjectManagement Professional (PMP) certification is a plus. Familiaritywith project management tools and methodologies.