Senior Machine Learning Engineer
- Compensation
- Not disclosed
- Location
- Los Angeles, California, United States
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- - A Bachelors degree in Computer Science, Statistics, Mathematics, or a related field, with a preference for advanced degrees.
- - At least 5 years of experience in crafting ML training and inference pipelines using MLFlow, Kubeflow on GCP.
- - Profound knowledge of machine learning frameworks, libraries, data structures, data modeling, and software architecture.
- - Proficiency in programming languages such as Python, Java, Scala.
- - Practical experience with machine learning algorithms, processes, tools, and platforms, including Python, TensorFlow, PyTorch, etc.
- - Familiarity with cloud services (GCP, AWS, Azure).
- - Exceptional problem-solving abilities and teamwork skills.
- Additional Skills:
- - Implementation of data quality checks and governance processes to ensure data integrity and compliance with privacy and security regulations.
- - Optimization of pipelines and queries for enhanced performance and scalability.
- - Effective collaboration with cross-functional teams to meet data requirements.
- - Continuous learning and evaluation of new data engineering technologies and tools.
Nice to have
- - Experience with data streaming technologies like Apache Kafka.
- - Knowledge in ELT and ETL processes for feature extraction.
- - Proficiency in data visualization tools such as Tableau, Power BI.
- - Certifications in relevant data engineering technologies.
- This role is crucial for developing our data infrastructure and ensuring the availability and reliability of data for analysis. Your expertise in data engineering will be instrumental in driving our o
Full description
Our client is on a mission to transform healthcare using the power of artificial intelligence. We are dedicated to leveraging AI to make a significant impact on healthcare, aiming to enhance patient care by making every patient's journey a cornerstone for healthcare decisions. Our goal is to improve treatment outcomes and accelerate drug discovery by analyzing patient health records to provide accurate and timely care. If you are passionate about advancing healthcare through innovative technology, we invite you to join us in pioneering the future.
Role Overview:
In the role of Senior Machine Learning Engineer, you will play a pivotal role in our data team, tasked with the design, construction, and maintenance of ML pipelines and services. Your main responsibilities will include the development and refinement of ML training and inference pipelines, ensuring their efficiency, reliability, and accessibility to boost AI practitioner productivity and reduce cycle times. Collaborating closely with product engineers, data scientists, analysts, and other key stakeholders, you will support data-driven decision-making and enhance business intelligence.
Key Responsibilities:
- Engineer, implement, and deploy machine learning models into live environments.
- Construct and maintain robust ML training and inference pipelines utilizing MLFlow and Kubeflow.
- Collaborate with the data science team to scale their algorithms effectively.
- Guarantee the performance, quality, and responsiveness of deployed models.
- Work alongside cross-functional teams to conceptualize, design, and launch new functionalities.
- Proactively explore, assess, and integrate new technologies to enhance development efficiency.
Qualifications:
- A Bachelors degree in Computer Science, Statistics, Mathematics, or a related field, with a preference for advanced degrees.
- At least 5 years of experience in crafting ML training and inference pipelines using MLFlow, Kubeflow on GCP.
- Profound knowledge of machine learning frameworks, libraries, data structures, data modeling, and software architecture.
- Proficiency in programming languages such as Python, Java, Scala.
- Practical experience with machine learning algorithms, processes, tools, and platforms, including Python, TensorFlow, PyTorch, etc.
- Familiarity with cloud services (GCP, AWS, Azure).
- Exceptional problem-solving abilities and teamwork skills.
Additional Skills:
- Implementation of data quality checks and governance processes to ensure data integrity and compliance with privacy and security regulations.