Job Description: Machine Learning Engineer

About the Role

We are seeking a highly skilled Machine Learning Engineer to join our data science and AI team. The ideal candidate will design, develop, and deploy scalable machine learning models to solve complex business problems, optimize decision-making, and improve user experiences. This role requires strong technical expertise in machine learning, data engineering, and software development, with the ability to work collaboratively across teams.

Key Responsibilities

Design, build, and optimize machine learning models for classification, regression, recommendation, natural language processing, and computer vision tasks.

Develop scalable data pipelines for model training, evaluation, and deployment.

Collaborate with data scientists, software engineers, and product managers to translate business requirements into machine learning solutions.

Implement and maintain model monitoring, performance tracking, and retraining pipelines.

Conduct experiments, perform feature engineering, and evaluate models using statistical and machine learning techniques.

Deploy models into production environments using frameworks such as TensorFlow Serving, PyTorch, or cloud-based ML services.

Ensure compliance with data governance, privacy, and security standards.

Stay up to date with advancements in AI/ML research and industry best practices, integrating relevant innovations into projects.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, or a related field.

Proven experience as a Machine Learning Engineer or a similar role in applied machine learning.

Strong programming skills in Python and proficiency with libraries such as TensorFlow, PyTorch, scikit-learn, and pandas.

Experience with data processing frameworks such as Apache Spark, Hadoop, or distributed computing systems.

Knowledge of cloud platforms (AWS, Google Cloud, or Azure) and containerization tools (Docker, Kubernetes).

Familiarity with MLOps practices, CI/CD pipelines, and model lifecycle management.

Strong understanding of algorithms, data structures, probability, and statistics.

Excellent problem-solving skills and the ability to work in a collaborative, fast-paced environment.

Preferred Skills

Experience with large language models (LLMs) and generative AI applications.

Background in deep learning architectures (CNNs, RNNs, Transformers).

Hands-on experience with vector databases, model explainability tools, or reinforcement learning.

Contributions to open-source ML projects or published research in machine learning.

What We Offer

Opportunity to work on cutting-edge AI/ML projects with real-world impact.

Competitive compensation and performance-based incentives.

Comprehensive health, dental, and vision benefits.

Professional development support, including conferences and certifications.

A collaborative culture that values innovation, creativity, and continuous learning.