Senior Platform ML Engineer [28836]

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Overview

The Senior Platform ML Engineer at Stealth will take a critical role in designing, developing, and deploying machine learning systems that enhance the functionality and efficiency of our platform. This position involves working collaboratively with cross-functional teams to create robust ML models, optimizing their performance, and ensuring their integration with existing technology. The ideal candidate should possess a strong foundation in machine learning frameworks, programming, and cloud services, bringing innovative solutions to complex engineering challenges.

Job Responsibilities

• Design and implement scalable machine learning algorithms and models suitable for production environments.
• Collaborate with data engineers and software developers to integrate ML solutions into platforms and applications.
• Conduct experiments to evaluate model performance and optimize hyperparameters for improved accuracy.
• Deploy and manage ML pipelines using cloud services and automation tools.
• Maintain documentation and provide technical guidance to junior team members.
• Identify and troubleshoot issues in machine learning processes and data flows.
• Stay abreast of the latest advancements in ML technologies and apply them to enhance current systems.

Qualifications

• Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 5+ years of professional experience in machine learning engineering or data science.
• Proficiency in programming languages such as Python, Java, or C++.
• Strong experience with machine learning frameworks like TensorFlow or PyTorch.
• Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud) for deploying ML models.
• Solid understanding of software engineering principles and best practices.
• Excellent problem-solving abilities and a keen analytical mindset.

Technologies & Tools

The Senior Platform ML Engineer will work with a variety of technologies and tools including but not limited to machine learning frameworks (TensorFlow, Keras, PyTorch), programming languages (Python, Java), cloud services (AWS, Azure, Google Cloud), and data processing tools (Apache Spark, Kafka). Familiarity with version control systems such as Git, CI/CD pipelines, and containerization technologies like Docker and Kubernetes is also essential.

Ideal Candidates

Ideal candidates for the Senior Platform ML Engineer position should demonstrate a blend of technical knowledge, hands-on experience, and effective communication skills. They should possess a strong aptitude for innovation, showcasing a proactive approach to solving disparate engineering challenges. Successful candidates will also thrive in collaborative environments, exhibit leadership qualities, and be committed to the continuous improvement and advancement of their technical expertise.