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Job Description

Description :

Requirements :


- Bachelor's/Master's / PhD in Computer Science or related field.

- 4+ years of hands-on experience as a Machine Learning Engineer or Architect.

- With a strong portfolio of deployed ML models for batch, streaming, and real-time use cases.

- Proficient in Python for model development and data manipulation, and experience with Java or Scala for building production systems.

- Familiarity with messaging queues (e. g., Kafka, SQS) and MLOps tools (e. g., MLflow, Kubeflow, Airflow).

- Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization (Docker, Kubernetes).

- Knowledge of machine learning frameworks (e. g., TensorFlow, PyTorch) and data stores (e. g., Elasticsearch, MongoDB, PostgreSQL).

- Knowledge of data processing and ETL tools (e. g., Apache Spark, Kafka).

- Experience in monitoring tools Grafana and Prometheus.

- Strong problem-solving skills and analytical mindset.

Preferred Qualifications :


- Experience in large-scale production systems and distributed computing.

- Contributions to open-source projects or active participation in the ML community.

- Demonstrated leadership capabilities and experience in mentoring junior engineers.

- Innovative mindset with a track record of developing solutions leading to significant business improvements or patents.

- A collaborative approach to working across multiple products and application teams.

- A willingness to learn, share, and improve continuously.


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