What are the responsibilities and job description for the ML Engineer / MLOps / Machine Learning Engineer / AI/ML position at Aptino?
Role: ML Architect / AI Architect
Location: Malvern, PA (Hybrid – 3 days / week from office)
Job Description:
We are looking for a Machine Learning Architect with strong hands-on experience in Databricks to design, build, deploy, and optimize machine learning solutions. The ideal candidate should have practical experience developing ML models using the Databricks Lakehouse Platform, leveraging MLflow, feature engineering, model training, and MLOps to deliver scalable AI/ML solutions.
Required Skills
- 5 years of experience in Machine Learning or AI development.
- Strong hands-on experience with Databricks Machine Learning.
- Experience using MLflow for experiment tracking, model registry, and deployment.
- Strong proficiency in Python.
- Experience with PySpark and Apache Spark.
- Knowledge of supervised and unsupervised machine learning algorithms.
- Experience building and deploying end-to-end ML pipelines.
- Hands-on experience with feature engineering, model evaluation, and hyperparameter tuning.
- Experience working in cloud environments AWS.
- Build and maintain production grade AWS applications (Lambda, S3, Glue, ECS/EKS, Step Functions, Bedrock, SageMaker).
- Develop and automate end to end data and ML pipelines using Spark/PySpark, Glue, Airflow, or dbt.
- Strong SQL skills and experience working with large-scale datasets.
Preferred Skills
- Experience with Databricks Lakehouse architecture.
- Knowledge of Generative AI, LLMs, or Retrieval-Augmented Generation (RAG) is a plus.
- Experience with orchestration tools such as Airflow or Azure Data Factory.
- Familiarity with Docker, Kubernetes, and CI/CD pipelines.
- Experience with Delta Lake and Unity Catalog.
Qualifications
- Bachelor''''''''s or Master''''''''s degree in Computer Science, Data Science, Engineering, or a related field.
- Databricks certification (preferred).