Machine Learning Engineer

Job Description :

We are seeking a skilled MLOps Specialist to join our team. As an MLOps Specialist, you will be responsible for bridging the gap between machine learning development and production deployment.

This role involves designing, developing, and implementing CI/CD pipelines for automating the deployment of machine learning models to production environments.

You will work closely with data scientists, software engineers, and business stakeholders to ensure that ML models are deployed, monitored, and scaled effectively.

Your key responsibilities will include:

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• Model Deployment : Design, develop, and implement CI/CD pipelines for automating the deployment of machine learning models to production environments.">
• Model Monitoring & Management : Build tools to monitor model performance in real-time and trigger automatic re-training when model drift occurs.">
• Collaboration : Work closely with data scientists and software engineers to ensure smooth integration of ML models into production.">
• Automation : Automate model training, deployment, and lifecycle management processes to improve efficiency and reduce manual overhead.">
• Cloud & Infrastructure Management : Manage cloud resources (AWS, GCP, Azure) and infrastructure to ensure high availability, cost optimization, and efficient scaling of ML workloads.">
• Versioning & Experiment Tracking : Implement versioning systems for model artifacts, datasets, and training environments.">
• Security & Compliance : Ensure that the deployed models meet security and regulatory requirements (data privacy, model governance, etc.).">
• Troubleshooting & Optimization : Debug and troubleshoot production ML models, and optimize performance issues related to compute, data pipelines, and model inference.">

Required Skills and Qualifications :

To be successful in this role, you will need:

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• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.">
• 3+ years of experience in deploying and maintaining machine learning models in production environments.">
• Experience working with cloud platforms like AWS, GCP, or Azure, and understanding of cloud-native services such as EC2, Lambda, Kubernetes, etc.">
• Proficiency in programming languages such as Python, R, or Java.">
• Strong understanding of machine learning workflows and tools such as TensorFlow, PyTorch, Scikit-learn, or similar.">
• Experience with containerization and orchestration technologies (Docker, Kubernetes).">
• Familiarity with version control systems (e.g., Git) and ML versioning tools (e.g., DVC, MLflow).">
• Expertise in creating and managing CI/CD pipelines using tools like Jenkins, GitLab CI, or CircleCI.">
• Experience with automated model testing, validation, and deployment.">
• Strong knowledge of infrastructure-as-code (IaC) tools such as Terraform or CloudFormation.">
• Monitoring & Observability : Experience with monitoring tools (Prometheus, Grafana, ELK stack) and logging frameworks for ML models in production.">
• Data Engineering : Familiarity with data pipelines (ETL) and distributed computing (Spark, Kafka).">
• Collaboration : Strong ability to work with cross-functional teams including data scientists, software engineers, and business stakeholders.">

Preferred Qualifications :

The following qualifications are highly desirable:

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• Advanced ML Tools : Knowledge of tools like Kubeflow, Seldon, or TFX for automating ML pipelines.">
• Data Security : Understanding of secure deployment practices for machine learning models, including data privacy and compliance standards (GDPR, HIPAA, etc.).">
• Model Interpretability : Familiarity with techniques for explaining and interpreting machine learning models (e.g., SHAP, LIME).">
• AI/ML Experimentation : Experience with experiment tracking platforms (e.g., Weights & Biases).">
• Leadership : Experience mentoring or leading teams in MLOps practices.">

Benefits :

We offer a competitive salary and benefits package, including opportunities for professional growth and development.

How to Apply :

Please submit your resume and cover letter to apply for this position.

Contact Us :

If you have any questions about this position, please contact us at [insert contact information].

About Us :

We are a company dedicated to innovation and excellence in the field of artificial intelligence and machine learning.

Our Culture :

We value diversity, equity, and inclusion in our workplace and strive to create a culture that is welcoming and supportive of all employees.

Disclaimer :

This job description is not intended to be a comprehensive list of all duties, responsibilities, or qualifications required of the employee in this role.

Keyword :

MLOps