Compunnel, Inc.
We are seeking a highly skilled and motivated Machine Learning Engineer to join our growing ML/AI practice.
This role focuses on enhancing machine learning systems for recommendation and personalization applications.
The ideal candidate will have hands-on experience in model development, performance evaluation, and production deployment, and will collaborate with cross-functional teams to deliver impactful AI solutions.
Key Responsibilities
Iterate on existing ML models to improve performance, efficiency, and feature integration.
Benchmark models and enhance blending strategies for multiple prediction sources.
Evaluate model performance using offline metrics and online experiment data.
Conduct subgroup analysis to identify areas for KPI improvement.
Enhance model explainability to support product and business decision-making.
Collaborate with data scientists, backend engineers, and other stakeholders.
Contribute to AI model development and deployment using tools like Databricks, MLflow, and Seldon.
Participate in code reviews and ensure adherence to coding standards.
Drive innovation by proposing new ideas and improvements to data infrastructure and processes.
Required Qualifications
Minimum 3 years of experience in machine learning or data science teams (excluding research/R&D roles). Minimum 5 years of experience programming in Python or Scala. Minimum 5 years of experience with ML libraries and frameworks (e.g., TensorFlow, PySpark). At least 1 year of experience with Databricks, MLflow, or Seldon. Strong understanding of recommendation algorithms and machine learning principles. Experience with cloud services (e.g., AWS) and software engineering best practices. Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Preferred Qualifications
Proven track record of delivering large-scale commercial ML products. Experience with Snowflake, Kubeflow, Tecton, Jenkins. Background in building customer-facing ML applications, especially recommendation systems. Familiarity with custom ML platforms, feature stores, and model monitoring. Knowledge of A/B testing, causal inference, and ML best practices. Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, Data Science, or a related field. Email ID * This field is required Please enter valid emailId. Cell phone * This field is required Please enter valid cell phone. First Name * This field is required Please enter valid first name. Last Name * This field is required Please enter valid last name.
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Minimum 3 years of experience in machine learning or data science teams (excluding research/R&D roles). Minimum 5 years of experience programming in Python or Scala. Minimum 5 years of experience with ML libraries and frameworks (e.g., TensorFlow, PySpark). At least 1 year of experience with Databricks, MLflow, or Seldon. Strong understanding of recommendation algorithms and machine learning principles. Experience with cloud services (e.g., AWS) and software engineering best practices. Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Preferred Qualifications
Proven track record of delivering large-scale commercial ML products. Experience with Snowflake, Kubeflow, Tecton, Jenkins. Background in building customer-facing ML applications, especially recommendation systems. Familiarity with custom ML platforms, feature stores, and model monitoring. Knowledge of A/B testing, causal inference, and ML best practices. Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, Data Science, or a related field. Email ID * This field is required Please enter valid emailId. Cell phone * This field is required Please enter valid cell phone. First Name * This field is required Please enter valid first name. Last Name * This field is required Please enter valid last name.
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