AI Machine Learning Engineer

We are seeking a highly skilled AI / Machine Learning Engineer to design build and deploy intelligent systems that enhance decision-making automation and product capabilities. The ideal candidate will have strong experience in machine learning deep learning data engineering practices and cloud-based model deployment.

• Develop train and optimize ML and deep learning models using Python and modern frameworks (TensorFlow PyTorch Scikit-learn).

• Build scalable end-to-end pipelines for data ingestion preprocessing feature engineering model training validation and deployment.

• Research prototype and implement new algorithms for computer vision NLP predictive analytics and generative AI.

• Collaborate with data engineers product teams and software developers to integrate ML solutions into production systems.

• Deploy and manage models using cloud platforms (AWS GCP Azure) and MLOps tools.

• Monitor model performance drift and quality; maintain continuous improvements through retraining and tuning.

• Work with large-scale datasets to extract insights and improve predictive accuracy.

• Document models experiments and architecture clearly for cross-functional teams.

• Ensure ML systems follow best practices for security compliance and ethical AI standards.

• Bachelors or Masters degree in Computer Science Data Science AI Machine Learning or related field.

• Strong hands-on experience with Python TensorFlow PyTorch Keras Scikit-learn etc.

• Solid understanding of machine learning algorithms deep learning architectures (CNNs RNNs Transformers).

• Experience with cloud platforms : AWS (SageMaker) GCP (Vertex AI) or Azure ML.

• Strong knowledge of SQL data structures algorithms and statistics.

• Experience building APIs and deploying ML models using Docker Kubernetes or serverless technologies.

• Familiarity with MLOps pipelines MLflow Kubeflow or similar tools.

• Ability to work with large datasets and use tools like Spark Databricks or Snowflake.

• Excellent problem-solving and analytical skills.

• Experience with Generative AI LLM fine-tuning RAG vector databases (Pinecone FAISS).

• Experience in NLP tasks like summarization sentiment analysis entity extraction or embeddings.

• Experience with real-time model inference or streaming data (Kafka Flink).

• Knowledge of reinforcement learning or optimization techniques.

• Publications Kaggle experience open-source contributions.

• Strong communication and documentation skills.

• Ability to collaborate with cross-functional teams.

• Self-driven curious and highly innovative mindset.

• Ability to work in an agile environment.

• Competitive salary and performance bonuses.

• Healthcare dental and retirement plans.

• Remote/hybrid work options.

• Professional development certifications and conference sponsorship.