Machine Learning Engineer

Company Information

At Advarra, we are passionate about making a difference in the world of clinical research and advancing human health. With a rich history rooted in ethical review services combined with innovative technology solutions and deep industry expertise, we are at the forefront of industry change. A market leader and pioneer, Advarra breaks the silos that impede clinical research, aligning patients, sites, sponsors, and CROs in a connected ecosystem to accelerate trials.

Company Culture 

Our employees are the heart of Advarra. They are the key to our success and the driving force behind our mission and vision. Our values (Patient-Centric, Ethical, Quality Focused, Collaborative) guide our actions and decisions. Knowing the impact of our work on trial participants and patients, we act with urgency and purpose to advance clinical research so that people can live happier, healthier lives. 

At Advarra, we seek to foster an inclusive and collaborative environment where everyone is treated with respect and diverse perspectives are embraced. Treating one another, our clients, and clinical trial participants with empathy and care are key tenets of our culture at Advarra; we are committed to creating a workplace where each employee is not only valued but empowered to thrive and make a meaningful impact.

Job Overview Summary 

As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning models and systems to enhance clinical study optimization. You will work closely with data scientists, data engineers, and other stakeholders to build scalable and efficient machine learning solutions that drive business value. Your expertise will be crucial in integrating machine learning models into production environments and ensuring their performance and reliability. Your work will be instrumental in shaping and executing a product roadmap that leverages cutting-edge data science methodologies, scalable infrastructure, and a strategic vision to drive innovation, business growth, and industry-wide adoption. 

Job Duties & Responsibilities 

• Machine Learning & Model Deployment: Design, develop, and implement machine learning models and algorithms to solve complex business problems. 
• System Integration: Integrate machine learning models into production systems, ensuring scalability, efficiency, and reliability. 
• Collaboration: Work closely with data scientists, data engineers, and software engineers to develop end-to-end machine learning solutions. 
• Data Pipeline: Build and maintain data pipelines for data ingestion, processing, and storage to support machine learning workflows. 
• Performance Monitoring: Monitor and evaluate the performance of machine learning models in production, making improvements as needed. 
• Documentation: Document machine learning processes, models, and systems to ensure reproducibility and knowledge sharing. 
• Cross functional Collaboration: Works with Software Engineering, Software Test, Data Engineering and Cloud teams to ensure Product priorities are well defined and planned for. 
• Continuous Improvement: Stay updated with the latest advancements in machine learning and apply them to improve existing models and systems. 

Location 

• This role is open to candidates working hybrid or remotely in India, Ireland, or the United States. 

Basic Qualifications

• Bachelor’s degree in data science, computer science, statistics, or a related field. 
• 3+ years of experience in machine learning engineering or a related field.
• Proficiency in programming languages such as Python, Java, or C++. 
• Experience building and deploying end-to-end data science and analytics solutions, including infrastructure, tools, and applications. 
• Strong understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch). 
• Experience with cloud-based platforms (e.g., AWS, Azure). 
• Excellent problem-solving and analytical skills. 
• Strong communication and teamwork abilities. 
• Demonstrated experience in Agile methodologies and best practices. 

Preferred Qualifications 

• Master’s degree in a relevant field such as data science, computer science, or statistics. 
• Strong proficiency in data science tools and languages, including R, Python, SQL, and Spark, and experience with machine learning frameworks (e.g., Pytorch, TensorFlow). 
• Hands-on experience in AWS for building and managing cloud-based analytics solutions. 
• Strong interpersonal and communication skills, with an ability to engage stakeholders and drive adoption of data-driven processes.