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.
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Design & Develop AI/ML Solutions:
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Build and deploy predictive and prescriptive models using Python, TensorFlow, PyTorch, or similar frameworks.
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Work on NLP, computer vision, recommendation systems, or other applied AI projects.
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Data Engineering & Analytics:
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Develop and optimize data ingestion, transformation, and analysis pipelines.
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Use SQL and Java to process, clean, and analyze large structured/unstructured datasets.
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Integrate data-driven models into enterprise applications.
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Software Development:
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Build backend components and APIs using Java (Spring Boot or similar frameworks).
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Collaborate with DevOps teams to deploy models into production environments.
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Business Problem Solving:
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Work closely with business teams to understand objectives and translate them into AI/ML solutions.
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Generate insights from data to support data-driven decision-making.
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Performance Optimization & Monitoring:
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Tune model accuracy and application performance.
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Automate model retraining and monitoring pipelines.
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Qualifications:
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Experience Required: 5 to 8 years
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Education:
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Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
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Core Technical Skills:
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AI / ML: Scikit-learn, TensorFlow, Keras, PyTorch, NLP frameworks.
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Programming: Strong in Java, good proficiency in Python and SQL.
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Data Handling: Experience with relational databases (MySQL, PostgreSQL, Oracle) and data visualization tools (Power BI, Tableau, or Matplotlib).
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APIs & Integration: RESTful API development and integration of ML models with Java applications.
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Big Data (Optional but Preferred): Exposure to Spark, Hadoop, or Kafka.
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Soft Skills:
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Strong problem-solving and analytical thinking.
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Excellent communication and teamwork skills.
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Ability to mentor junior team members and collaborate in cross-functional teams.
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Preferred Experience:
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Experience in AI project lifecycle – data preparation, model building, deployment, and monitoring.
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Experience with MLOps tools (MLflow, Kubeflow, Docker, etc.).
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Familiarity with cloud platforms like AWS, Azure, or GCP.
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Experience working in Agile environments.
Additional Information:
All your information will be kept confidential according to EEO guidelines.
