Machine Learning Engineer
- Cradlepoint
- 10 - 15 years
- Kolkata
- 15 days ago
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Job Description
Join our Team
About this opportunity:
We are looking for a Senior Machine Learning Engineer with 10+ years of experience to design, build, and deploy scalable machine learning systems in production. This is not a data science role we are seeking an engineering-focused individual who can partner with data scientists to productionize models, own ML pipelines end-to-end, and drive reliability, automation, and performance of our ML infrastructure.
You ll work on mission-critical systems where robustness, monitoring, and maintainability are key. You should be experienced with modern MLOps tools, cloud platforms, containerization, and model serving at scale.
What you will do:
- Design and build robust ML pipelines and services for training, validation, and model deployment.
- Work closely with data scientists, solution architects, DevOps engineers, etc. to align the components and pipelines with project goals and requirements. Communicate deviation from target architecture (if any).
- Cloud Integration: Ensuring compatibility with cloud services of AWS, and Azure for enhanced performance and scalability
- Build reusable infrastructure components using best practices in DevOps and MLOps.
- Security and Compliance: Adhering to security standards and regulatory compliance, particularly in handling confidential and sensitive data.
- Network Security: Design optimal network plan for given Cloud Infrastructure under the E// network security guidelines
- Monitor model performance in production and implement drift detection and retraining pipelines.
- Optimize models for performance, scalability, and cost (e.g., batching, quantization, hardware acceleration).
- Documentation and Knowledge Sharing: Creating detailed documentation and guidelines for the use and modification of the developed components.
The skills you bring:
- Strong programming skills in Python
- Deep experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost).
- Hands-on with MLOps tools like MLflow, Airflow, TFX, Kubeflow, or BentoML.
- Experience deploying models using Docker and Kubernetes.
- Strong knowledge of cloud platforms (AWS/GCP/Azure) and ML services (e.g., SageMaker, Vertex AI).
- Proficiency with data engineering tools (Spark, Kafka, SQL/NoSQL).
- Solid understanding of CI/CD, version control (Git), and infrastructure as code (Terraform, Helm).
- Experience with monitoring/logging (Prometheus, Grafana, ELK).
Good-to-Have Skills
- Experience with feature stores (Feast, Tecton) and experiment tracking platforms.
- Knowledge of edge/embedded ML, model quantization, and optimization.
- Familiarity with model governance, security, and compliance in ML systems.
- Exposure to on-device ML or streaming ML use cases.
- Experience leading cross-functional initiatives or mentoring junior engineers.
Why join Ericsson
What happens once you apply
Primary country and city: India (IN) || Bangalore
Req ID: 770160
Job Classification
Industry: Software ProductFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data Platform EngineerEmployement Type: Full timeContact Details:
Company: CradlepointLocation(s): Kolkata+ View Contact
Keyskills: Automation Version control GIT NoSQL GCP Machine learning Network security Infrastructure SQL Python
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