Our company is committed to finding the best and the brightest talent to help us reach the top.

If you are a dynamic, highly skilled, experienced Cloud engineer and technology enthusiast, and you enjoy working in a rapid pace within a rapidly growing business environment, then you will want to consider this position.

If you excel at communication, collaboration, and unrelenting innovation, we want to talk to you.

And if you bring dedication, positive energy and integrity to the table, you just might be the right fit for our team.

Qualifications :

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.

The requirements listed below are representative of the knowledge, skill, and/or ability required.

Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

Roles & Responsibilities (Other Duties May Be Assigned) :

- Design, develop, and deploy robust & scalable AI/ML models in Production environments.

- Collaborate with business stakeholders to identify AI/ML opportunities and define measurable success metrics.

- Optimize models for performance, latency and scalability.

- Build data pipelines and workflows to support model training and evaluation.

- Conduct research & experimentation on the state of the art techniques (DL, NLP, Time series, CV).

- Partner with MLOps and DevOps teams to implement best practices in model monitoring, version and re-training.

- Lead code reviews, architecture discussions and mentor junior & peer engineers.

- Architect and implement end-to-end AI/ML pipelines, ensuring scalability and efficiency.

- Deploy models in cloud-based (AWS, Azure, GCP) or on-premise environments using tools like Docker, Kubernetes, TensorFlow Serving, or ONNX.

- Ensure data integrity, quality, and preprocessing best practices for AI/ML model development.

- Ensure compliance with AI ethics guidelines, data privacy laws (GDPR, CCPA), and corporate AI governance.

- Work closely with data engineers, software developers, and domain experts to integrate AI into existing systems.

- Conduct AI/ML training sessions for internal teams to improve AI literacy within the organization.

- Strong analytical and problem-solving mindset.

Technical Requirements :

- Strong expertise in AI/ML engineering and software development.

- Proficiency in Python and hands-on experience in using ML frameworks (tensorflow, pytorch, scikit-learn, xgboost etc).

- Solid understanding of AI/ML life cycle Data preprocessing, feature engineering, model selection, training, validation and deployment.

- Experience in production grade ML systems (Model serving, APIs, Pipelines).

- Familiarity with Data engineering tools (SPARK, Kafka, Airflow etc).

- Strong knowledge of statistical modeling, NLP, CV, Recommendation systems, Anomaly detection and time series forecasting.

- Hands-on in Software engineering with knowledge of version control, testing & CI/CD.

- Hands-on experience in deploying ML models in production using Docker, Kubernetes, TensorFlow Serving, ONNX, and MLflow.

- Experience in MLOps & CI/CD for ML pipelines, including monitoring, retraining, and model drift detection.

- Proficiency in scaling AI solutions in cloud environments (AWS, Azure & GCP).

- Experience in data preprocessing, feature engineering, and dimensionality reduction.

- Exposure to Data privacy, Compliance and Secure ML practices.

Experience and/or Education Qualification :

- Graduation or masters in computer science or information technology or AI/ML/Data science.

- 5-8 years of hands-on experience in AI/ML development/deployment and optimization