Role Description
We are seeking talented and motivated Data, Artificial Intelligence (AI), and Machine Learning (ML) Engineers
at
entry to mid-level
to join our growing technology and innovation team. In this role, you will work on designing, developing, and deploying data pipelines, machine learning models, and AI-driven solutions that help solve real-world business challenges and unlock new opportunities through data.
As a Data / AI / ML Engineer, you will be responsible for building robust data infrastructure, training and optimizing models, and collaborating closely with data scientists, analysts, and software engineers. Ideal candidates are technically strong, curious, and eager to learn emerging technologies in the AI/ML ecosystem, while contributing to impactful, production-grade solutions.
Whether you're a recent graduate with hands-on project experience or a mid-level professional looking to deepen your AI/ML engineering skills, this role provides a solid platform for growth, innovation, and real-world application of modern data science and engineering practices.
Key Responsibilities
Design, build, and maintain scalable
data pipelines
for data ingestion, transformation, and storage using tools like SQL, Python, Spark, or cloud-native services.
Collaborate with data scientists to
develop, test, and deploy ML models
into production environments.
Implement and support
machine learning workflows
including model training, evaluation, versioning, and monitoring.
Work with large-scale structured and unstructured datasets using modern data platforms (e.g., AWS, Azure, GCP, Databricks, Snowflake).
Apply
MLOps practices
to automate CI/CD pipelines for ML models and manage end-to-end lifecycle.
Assist in optimizing data models and algorithms for performance, scalability, and accuracy.
Research and prototype AI/ML algorithms, staying current with trends in deep learning, NLP, generative AI, and computer vision (as relevant).
Contribute to code quality through writing clean, modular, and well-documented code, using Git and Agile/Scrum methodologies.
Partner with cross-functional teams to understand business problems and translate them into technical solutions.
Participate in peer code reviews, technical discussions, and knowledge-sharing sessions.
Preferred Skills and Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
Proficiency in Python and common ML/data libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
Familiarity with cloud services (e.g., AWS SageMaker, GCP Vertex AI, Azure ML) is a plus.
Strong analytical, problem-solving, and communication skills.
Experience with version control (e.g., Git), containerization (e.g., Docker), and workflow orchestration (e.g., Airflow) is an advantage.
Eagerness to learn, adapt, and grow in a collaborative environment.
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