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