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Ericsson-Worldwide
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Machine Learning Engineer

Machine Learning Engineer

Ericsson-Worldwide

0 years

0 Lacs

Kolkata, West Bengal

Posted:1 week ago| Platform: Indeed logo

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Skills Required

learning design data engineering ml drive reliability automation monitoring containerization model training devops architecture integration aws azure security compliance network drift scalability quantization documentation modification programming tensorflow pytorch mlflow airflow docker gcp sagemaker vertex spark kafka sql git code terraform logging tracking governance mentoring

Work Mode

On-site

Job Description

Kolkata,West Bengal,India

+1 more

Job ID

770160

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?

At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What happens once you apply?

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Machine Learning Engineer