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 costeffective hardware configurations based on usecase 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 ScikitLearn SparkML) 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 problemsolving skills and a passion for tackling complex challenges.

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.