Machine Learning Engineer - ML Applications

Machine Learning Engineer - ML Applications

Description -

Job Summary

This role is responsible for specializing in development and deployment of machine learning models that drive innovation and business value. The role researches and implements appropriate ML algorithms and tools, runs machine learning tests and experiments, and trains and retrains systems when necessary. The role contributes to deploying models in production environments and ensuring their seamless integration.

Responsibilities

Develops and programs integrated software solutions, especially in support of the development, deployment and life cycle of machine learning models.

Trains and validates models using appropriate evaluation metrics and techniques.

Optimizes and tunes hyperparameters to improve model performance and generalization.

Deploys machine learning models to production environments, ensuring scalability, reliability, and efficiency.

Monitors and maintains deployed models, making necessary updates to adapt to changing data or requirements.

Spearheads the design of ML systems, experiments with ML algorithms, and regularly trains systems for maximum efficiency.

Designs, develops, tests, and maintains ML pipelines that efficiently produce scalable models.

Cooperates with CI/CD teams to ensure seamless deployment of models to production.

Partners with research and engineering teams to enhance automated model training techniques.

Applies machine learning and statistical modeling techniques to business or research problems.

Education & Experience Recommended

Four-year or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.

Typically has 4-7 years of work experience, preferably in computer programming languages, machine learning, algorithms, statistical methods, or a related field or an advanced degree with 3-5 years of work experience.

Preferred Certifications

AWS Certified Machine Learning Specialty

Knowledge & Skills

Agile Methodology

Algorithms

Amazon Web Services

Apache Spark

Artificial Intelligence

Automation

Big Data

C++ (Programming Language)

Computer Science

Data Science

Deep Learning

Java (Programming Language)

Machine Learning

Microsoft Azure

Natural Language Processing

Python (Programming Language)

PyTorch (Machine Learning Library)

Scikit-learn (Machine Learning Library)

Software Engineering

TensorFlow

Cross-Org Skills

Effective Communication

Results Orientation

Learning Agility

Digital Fluency

Customer Centricity

Impact & Scope

Impacts multiple teams and may act as a team or project leader providing direction to team activities and facilitates information validation and team decision making process.

Complexity

Responds to moderately complex issues within established guidelines.

Disclaimer

This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.

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Job -

Software

Schedule -

Full time

Shift -

No shift premium (Brazil)

Travel -

Relocation -

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