ML Ops
1 week ago
Job Title:
Machine Learning Engineer MLOpsSpecialistLocation: 100% RemotePermanent
RoleJob Description:
We are seeking a highly skilled and experienced MachineLearning Engineer with a strong focus on MLOps to join our dynamicIT team.
The ideal candidate should have a solid background inbuilding and deploying microservices for machine learning models adeep understanding of MLOps and expertise in implementing MLapplications with a keen eye on scalability performance andresilience.
Responsibilities:
MicroservicesDevelopment:
Developand maintain microservices for deploying machine learning models.
Ensure scalability performanceand resilience of microservices.
MLOps Implementation:
Implement and optimize MLOps practices tostreamline the machine learning model lifecycle.
Use tools such as Databricks (MLFlowFeature store) Sagemaker and Kubernetes for efficient MLOps.
ML ApplicationProductionization:
Productionize ML experiments with a focus on scalability andperformance.
Define featurestores implement versioning for model development and integrateacross platforms.
Advanced Model Capabilities:
Leverage advanced model capabilitiesincluding distributed model training.
Define embeddings for different model buildingcapabilities.
Hardware Configuration:
Recommend ideal and costeffective hardwareconfigurations based on usecase complexity and model requirements
Data Understandingand Modeling:
Conduct Exploratory Data Analysis (EDA) and contribute to effectivedata modeling
CodingBest Practices:
Adhere to best coding practices emphasizing modularity codecoverage reusability and abstractions
Data Visualization:
Utilize data visualizations for patternidentification clustering and addressing bias in machine learningmodels
TechStack:
Proficient inDatabricks Sagemaker AWS services (IAM EC2 EMR Lambda S3) Python RML Frameworks (TensorFlow PyTorch Keras ScikitLearn SparkML) SparkPySpark Kubernetes Docker Jenkins and Airflow.
Qualifications:
5 years of IT experience.
Outstanding Python skills (minimum 3years).Deep understanding ofMLOps (minimum 2 years).Experience in productionizing ML experiments.
Expertise in defining feature stores andversioning for model development.
Understanding of advanced model capabilities includingdistributed model training.
Knowledgeable in hardware configurations for machine learning.
Solid experience in EDA anddata modeling.
Fluent inEnglish with excellent verbal and written communication skills.
Strong problemsolving skillsand a passion for tackling complex challenges.
Qualifications:
5+ years of IT experience. Outstanding Pythonskills (minimum 3 years). Deep understanding of MLOps (minimum 2years). Experience in productionizing ML experiments. Expertise indefining feature stores and versioning for model development.
Understanding of advanced model capabilities, including distributedmodel training. Knowledgeable in hardware configurations formachine learning. Solid experience in EDA and data modeling. Fluentin English with excellent verbal and written communication skills.
Strong problem-solving skills and a passion for tackling complexchallenges.
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