Lead AI and Data Science Engineer

Lead-Infrastructure

Job Description

We are seeking an experienced AI and Data Science Engineer with a solid foundation in Java programming and SQL-based data management. The ideal candidate will design, develop, and deploy scalable AI-driven applications and data pipelines, integrating predictive analytics into enterprise systems.

• Design & Develop AI/ML Solutions:

  • Build and deploy predictive and prescriptive models using Python, TensorFlow, PyTorch, or similar frameworks.

  • Work on NLP, computer vision, recommendation systems, or other applied AI projects.

• Data Engineering & Analytics:

  • Develop and optimize data ingestion, transformation, and analysis pipelines.

  • Use SQL and Java to process, clean, and analyze large structured/unstructured datasets.

  • Integrate data-driven models into enterprise applications.

• Software Development:

  • Build backend components and APIs using Java (Spring Boot or similar frameworks).

  • Collaborate with DevOps teams to deploy models into production environments.

• Business Problem Solving:

  • Work closely with business teams to understand objectives and translate them into AI/ML solutions.

  • Generate insights from data to support data-driven decision-making.

• Performance Optimization & Monitoring:

  • Tune model accuracy and application performance.

  • Automate model retraining and monitoring pipelines.

Qualifications

• Experience Required: 5 to 8 years

• Education:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

• Core Technical Skills:

  • AI / ML: Scikit-learn, TensorFlow, Keras, PyTorch, NLP frameworks.

  • Programming: Strong in Java, good proficiency in Python and SQL.

  • Data Handling: Experience with relational databases (MySQL, PostgreSQL, Oracle) and data visualization tools (Power BI, Tableau, or Matplotlib).

  • APIs & Integration: RESTful API development and integration of ML models with Java applications.

  • Big Data (Optional but Preferred): Exposure to Spark, Hadoop, or Kafka.

• Soft Skills:

  • Strong problem-solving and analytical thinking.

  • Excellent communication and teamwork skills.

  • Ability to mentor junior team members and collaborate in cross-functional teams.

• Preferred Experience:

• Experience in AI project lifecycle – data preparation, model building, deployment, and monitoring.

• Experience with MLOps tools (MLflow, Kubeflow, Docker, etc.).

• Familiarity with cloud platforms like AWS, Azure, or GCP.

• Experience working in Agile environments.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Experience Level

Senior Level