AI/ ML Engineer with Gen AI Applications

Job Title: AIML Engineer ML Engineering, MLOps & GenAI

Company: Amzur Technologies

Location: Hyderabad / Bangalore / Visakhapatnam / Remote (India)

Experience: 5 – 10 Years ( 2 years in production-grade ML/AI systems)

Notice Period: Immediate to 30 Days (Preferred)

Employment Type: Full-Time

About the Role

We are looking for a hands-on AIML Engineer to join our GenAI & Advanced Analytics team. You will design, build, and deploy AI/ML systems from start to finish. You should have strong ML skills, software engineering experience, and a passion for building real-world AI solutions.

What You Will Do

ML Engineering

• Build, train, test, validate, and deploy ML models using Python, scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, etc.
• Perform feature engineering, model selection, and optimization.
• Use techniques like transfer learning, quantization, and mixed-precision training.
• Create pipelines for cloud and edge devices (Jetson Nano, TensorRT, ONNX Runtime).
• Use proper validation methods and write clean, reproducible code.

MLOps & Automation

• Build CI/CD pipelines for ML using MLflow, Kubeflow, TFX, DVC, BentoML.
• Automate model versioning, retraining, and drift detection.
• Deploy models using Docker, Kubernetes, Terraform, or CloudFormation.
• Monitor models in production and ensure governance.
• Work with cloud ML platforms like AWS SageMaker, GCP Vertex AI, or Azure ML (preferred).

Data Engineering & Pipelines

• Create data pipelines for training and inference using Spark, Kafka, Airflow.
• Analyze data (EDA) and maintain feature stores.
• Use tools like dbt, Apache Beam, Great Expectations, Prefect.
• Work with data lakes and warehouses: Delta Lake, Iceberg, Hudi, Snowflake, BigQuery.
• Collaborate with data teams to ensure data quality and pipeline reliability.

Generative AI & GenAI

• Build LLM-based solutions using LangChain, Hugging Face Transformers, OpenAI APIs.
• Implement RAG (Retrieval-Augmented Generation) and optimize prompts.
• Fine-tune LLMs (LoRA, QLoRA, instruction tuning) and manage hallucinations.
• Use GenAI to enhance ML systems like recommendations, summarization, and knowledge retrieval.

Software & Engineering Practices

• Follow Agile processes and SDLC best practices.
• Use Git for version control (branching, pull requests, code reviews).
• Automate testing for ML code and data validation.
• Create high-level data and model architecture diagrams.
• Integrate ML pipelines into software releases.

Skills Required

• Programming: Python, SQL, scripting languages.
• ML Frameworks: scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM.
• MLOps: MLflow, Kubeflow, DVC, TFX, BentoML.
• Data Tools: Spark, Kafka, Airflow, dbt, Great Expectations.
• Visualization: matplotlib, seaborn, Plotly, Tableau, Power BI.
• Monitoring: Prometheus, Grafana, ELK.
• Strong understanding of statistics, probability, and causal reasoning.

Preferred Skills

• Databricks Lakehouse / Vertex AI Pipelines.
• Bayesian modeling (PyMC3, Stan), time-series forecasting (ARIMA, Prophet).
• Responsible AI: fairness, bias detection, explainability (SHAP, LIME).
• Contributions to open-source ML/AI projects or research publications.

Qualifications

• Bachelor's / Master's / PhD in Computer Science, Data Science, Statistics, or related field.
• 6+ years of hands-on experience in ML Engineering, MLOps, and Data Engineering.
• Proven experience deploying and maintaining AI models at scale.

Why Join Us

• Work on cutting-edge AI & GenAI projects.
• Innovate using open-source and enterprise tools.
• Collaborative and learning-focused culture.
• Flexible remote/hybrid options.
• Competitive compensation and global exposure.