4735-1 machine learning engineer - level ii (3-5 years)

Descripción del cargo

We are searching for one of our clients a Machine Learning Software Engineers; a professional who specializes in designing, developing, and implementing software solutions that leverage machine learning technologies. Their role is essential in creating intelligent systems capable of learning from data, identifying patterns, and making decisions with minimal human intervention.

Responsibilities

Collaborate with data scientists to design and develop machine learning models and algorithms to solve specific business or operational problems.
Collaborate with data scientists and analysts to understand data requirements and implement scalable solutions.
Implement pipelines for data ingestion, feature extraction, model training, and inference.
Optimize machine learning models for performance, scalability, and efficiency.
Develop and deploy large-scale applications and services into production environments, ensuring they are scalable and able to handle real-time data.
Monitor and maintain applications in production, updating them as necessary to maintain accuracy and performance.
Collaborate with cross-functional teams (product managers, UX/UI designers, developers) to integrate machine learning features into broader software systems.
Stay up to date with the latest engineering technologies, frameworks, and best practices to continuously improve solution quality and efficiency.


Skills and Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
Strong programming skills in languages such as Python, Java, C++, or Scala.
Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
Understanding of machine learning algorithms and principles (e.g., supervised and unsupervised learning, deep learning, reinforcement learning).
Familiarity with data modeling and data engineering techniques.
Experience with cloud computing services (AWS, Google Cloud, Azure) for deploying machine learning models.
Ability to work with large datasets and implement scalable solutions.
Excellent problem-solving skills and the ability to work in a team environment.
Strong communication skills to effectively collaborate with team members and stakeholders.


Additional Requirements

Experience with version control systems such as Git.
Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes) is a plus.
Understanding of DevOps principles and practices for machine learning (MLOps) is beneficial.