Feuji - Machine Learning Engineer - Tensorflow/PyTorch

6 days ago

Hyderabad, Telangana, India hirist Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Note : If shortlisted, you will be invited for initial rounds on 8th November'25 (Saturday) in Hyderabad


Description :

Job Title : ML Engineer

Years of Experience : 4-6 Years

Company : Feuji Software Solutions Pvt Ltd.,

Mode of Hire : Permanent Position

Work Location : Hyderabad

About Feuji :

Feuji, established in 2014 and headquartered in Dallas, Texas, has rapidly emerged as a leading global technology services provider. With strategic locations including a Near Shore facility in San Jose, Costa Rica, and Offshore Delivery Center in Hyderabad, we are well-positioned to cater to a diverse clientele. Our team of 500 talented engineers drives our success, delivering innovative solutions to our clients and contributing to our recognition as a 'Best Place to Work For.'

We collaborate with a wide range of clients, from startups to industry giants in sectors like Healthcare, BFSI, Supply Chain, Pharma & Life science, enabling transformative changes in their operations. Through partnerships with top technology providers, we empower our clients' growth and innovation

With a clientele including Microsoft, HP, GSK, and DXC Technologies, we specialized in applied AI Engineering solutions, Quality Engineering, Cyber Security, and Data Engineering Solutions. We are helping our clients build value based GCC teams in nearshore & offshore.

Our commitment to creating 'Happy Teams' underscores our values and dedication to positive impact. Feuji welcomes exceptional talent to join our team, offering a platform for growth, development, and a culture of innovation and excellence.

JOB Specification :

Builds and deploys machine learning models across supervised, unsupervised, and deep learning use cases. Implements feature engineering, hyperparameter tuning, and model evaluation, while maintaining automated training and deployment pipelines using tools like MLflow, Kubeflow, and Airflow.

Ensures production reliability through continuous monitoring, performance tracking, and data pipeline optimization.

Key Responsibilities :

ML Model Development :

- Develop and deploy ML models (supervised, unsupervised, deep learning).

- Perform feature engineering, model selection, and hyperparameter tuning.

- Implement model evaluation and interpretability techniques (SHAP, LIME).

MLOps & ML Infrastructure :

- Build and maintain ML pipelines : training ? validation ? deployment.

- Implement experiment tracking and model versioning (MLflow, W&B or Neptune).

- Deploy models using serving infrastructure (TensorFlow Serving, TorchServe, Triton, BentoML).

- Work with ML orchestration tools (Kubeflow, Airflow, Metaflow).

- Support A/B testing and model deployment strategies.

Model Monitoring & Alerting :

- Implement monitoring for model performance : latency, accuracy, drift detection.

- Build dashboards (Grafana, Kibana, CloudWatch) and configure alerts (Slack, PagerDuty).

- Log predictions and actuals for continuous monitoring.

Data Engineering :

- Write efficient SQL : joins, aggregations, CTEs, window functions.

- Work with cloud data platforms (Databricks, Snowflake, BigQuery, Redshift, Synapse).

- Build ETL/ELT pipelines using AWS Glue, dbt, or Airflow.

Platform Engineering & Observability :

- Contribute to ML platforms on Kubernetes/EKS.

- Monitor cloud costs and resource consumption.

Required Skills :

Strong hands-on experience.

ML & Data Science

- EDA and ML algorithms : regression, classification, clustering, ensembles (XGBoost, LightGBM, CatBoost).

- Experience with any deep learning framework : TensorFlow, PyTorch, or Keras.

- Model evaluation and cross-validation techniques.

MLOps :

- Hands-on with experiment tracking (any of MLflow, W&B, Neptune).

- Experience with model serving (any of TorchServe, Triton, BentoML, KServe).

- Familiarity with ML orchestration (any of Kubeflow, Airflow, Prefect, Metaflow).

- Docker and basic Kubernetes knowledge.

Programming & Automation :

- Strong Python programming.

- Basic Bash scripting.

- Debugging and troubleshooting skills.

Nice to Have Skills :

- Cloud platforms : AWS/GCP/Azure (SageMaker, Vertex AI, Azure ML).

- Feature stores (Feast, Tecton, SageMaker Feature Store).

- Model optimization (quantization, pruning, distillation).

- Distributed training (Horovod, PyTorch DDP, Ray).

- Open-source ML contributions.

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