AI ML Engineer

Job Summary

We are seeking a seasoned AI/ML Engineer to design, implement, and maintain machine learning models that power our next‑generation analytics platform. The role requires close collaboration with data scientists, product managers, and software engineers to transform experimental prototypes into scalable, production‑grade solutions that deliver measurable business value.

Key Responsibilities

• Lead end‑to‑end development of supervised and unsupervised ML models, from data preprocessing to model validation and deployment.
• Design and maintain robust data pipelines using Apache Airflow, Spark, or similar frameworks to ingest, clean, and transform large datasets.
• Collaborate with cross‑functional teams to define model requirements, performance metrics, and success criteria for new features.
• Implement automated testing, monitoring, and logging for deployed models to ensure reliability, drift detection, and compliance with data privacy standards.
• Document model architecture, data lineage, and decision logic to support reproducibility and knowledge transfer across the engineering organization.

Required Qualifications

• Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field, with a minimum of 3 years of professional experience in machine learning engineering.
• Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit‑learn.
• Hands‑on experience deploying models to cloud platforms (AWS SageMaker, GCP Vertex AI, or Azure ML) and managing model lifecycle.
• Strong understanding of version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes) for model deployment.

Preferred Qualifications

• Advanced degree (M.S. or Ph.D.) in Machine Learning, Data Science, or a related discipline.
• Experience with deep learning architectures (CNNs, RNNs, Transformers) and large‑scale training on GPU clusters.
• Knowledge of data privacy regulations (GDPR, CCPA) and experience building privacy‑preserving ML solutions.

Required Skills

• Python programming and familiarity with NumPy, Pandas, and Matplotlib.
• Machine learning model development using TensorFlow, PyTorch, or Scikit‑learn.
• Data pipeline construction with Apache Spark, Airflow, or AWS Glue.
• Model deployment on cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
• Containerization (Docker) and orchestration (Kubernetes).
• Version control with Git and CI/CD practices.
• Model monitoring and observability using Prometheus, Grafana, or similar tools.
• Strong analytical and problem‑solving skills with a focus on reproducibility and documentation.

Education

Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related technical field.

Benefits

• Competitive salary and equity package with annual performance bonuses.
• Comprehensive health, dental, and vision insurance plans for employees and dependents.
• Flexible work hours and generous paid time off, including remote work options.
• Professional development stipend and access to industry conferences, courses, and certifications.