ML Ops

This is a remote position.

Job Title: Machine Learning Engineer - MLOps Specialist

Location: 100% Remote

Permanent Role

Job Description:

We are seeking a highly skilled and experienced Machine Learning Engineer with a strong focus on MLOps to join our dynamic IT team. The ideal candidate should have a solid background in building and deploying microservices for machine learning models, a deep understanding of MLOps, and expertise in implementing ML applications with a keen eye on scalability, performance, and resilience.

Responsibilities:

Microservices Development:

Develop and maintain microservices for deploying machine learning models.

Ensure scalability, performance, and resilience of microservices.

MLOps Implementation:

Implement and optimize MLOps practices to streamline the machine learning model lifecycle.

Use tools such as Databricks (MLFlow, Feature store), Sagemaker, and Kubernetes for efficient MLOps.

ML Application Productionization:

Productionize ML experiments with a focus on scalability and performance.

Define feature stores, implement versioning for model development, and integrate across platforms.

Advanced Model Capabilities:

Leverage advanced model capabilities, including distributed model training.

Define embeddings for different model building capabilities.

Hardware Configuration:

Recommend ideal and cost-effective hardware configurations based on use-case complexity and model requirements.

Data Understanding and Modeling:

Conduct Exploratory Data Analysis (EDA) and contribute to effective data modeling.

Coding Best Practices:

Adhere to best coding practices, emphasizing modularity, code coverage, reusability, and abstractions.

Data Visualization:

Utilize data visualizations for pattern identification, clustering, and addressing bias in machine learning models.

Tech Stack:

Proficient in Databricks, Sagemaker, AWS services (IAM, EC2, EMR, Lambda, S3), Python, R, ML Frameworks (TensorFlow, PyTorch, Keras, Scikit-Learn, Spark-ML), Spark, PySpark, Kubernetes, Docker, Jenkins, and Airflow.

Requirements

Qualifications:

5+ years of IT experience.

Outstanding Python skills (minimum 3 years).

Deep understanding of MLOps (minimum 2 years).

Experience in productionizing ML experiments.

Expertise in defining feature stores and versioning for model development.

Understanding of advanced model capabilities, including distributed model training.

Knowledgeable in hardware configurations for machine learning.

Solid experience in EDA and data modeling.

Fluent in English with excellent verbal and written communication skills.

Strong problem-solving skills and a passion for tackling complex challenges.