About G2 - The Company
G2 is where you go for software. When you join us, you join the global team behind the largest and most trusted software marketplace. Every month, 5.5 million people come to G2 to inform smarter software decisions based on honest peer reviews. Authenticity is our focus, and every day we help thousands of companies, and hundreds of employees, propel their potential. Ready for meaningful work that starts and ends with compassion and heart? You’ve come to the right place.
G2 is going through exciting growth! We’ve recently secured our Series D funding of $157 million, which will further allow us to grow and develop our product and people. Read about it here!
About G2 - Our People
G2 was founded to create a place where people will love to work. We have big goals, and are grounded in our PEAK values—high performance and entrepreneurship, while also being authentic and kind. Employees are led by conscious leaders who are connected by shared commitments and 7 core leadership principles. We celebrate each other's successes, forgive mistakes, and support one another during challenging times. Together, we will grow and reach the top, while staying true to our values, ethics, and people.
As we foster our high-performance and entrepreneurial culture, we strive to create meaning in work and provide more than just a job: a true calling. At the heart of our community and culture are our people. Our global G2 team comes from a wide range of backgrounds and experiences, and that’s what makes our G2 community strong and vibrant. We want everyone to bring their authentic selves to work, and we do this through our company and team events, our G2 Gives charitable initiatives, and our Employee Resource Groups (ERGs).
We support our employees by offering generous benefits, such as flexible work, ample parental leave. Click here to learn more about our benefits.
This is a hybrid position, with the team meeting in person two days a week at our Bengaluru office.
About the Role
As a Senior Machine Learning Engineer, you'll play a key role in deploying machine learning models, establishing efficient MLOps practices, driving data engineering initiatives, and developing a scalable ML platform. Your responsibilities include deploying models seamlessly into production systems, optimizing them for performance, architecting MLOps pipelines for streamlined operations, and establishing a robust ML platform.
In this role, you will:-
Data/ML Pipelines and Deployment:
- Own the end-to-end deployment process for ML models, ensuring seamless integration into production systems.Optimize models for performance, scalability, and resource efficiency.Drive data engineering efforts, designing and optimizing scalable data pipelines for machine learning services.Develop and maintain robust ML/Data engineering processes, ensuring high data quality and reliability.
- Work with cross-functional teams to integrate the machine learning services into the product.
MLOps and Platform:
- Lead the design and implementation of a scalable ML platform, facilitating efficient model development and deployment.Architect infrastructure in support of rapid experimentation and evolving requirements.Implement CI/CD pipelines to ensure continuous integration and deployment of ML models.
- Establish MLOps pipelines, automating model training, deployment, and monitoring processes.
- Implement engineering standards and best practices.
Mentorship and Guidance (20%):
- Provide technical guidance to the team, enabling skill development and fostering best practices.Guide the data science team with the latest MLOps practices.
- Collaborate with larger engineering team to facilitate brainstorming sessions and ideate on platform best practices
Requirements:-
- 6+ years of experience in the field of machine learning engineering.
- 4+ years of hands-on experience in deploying ML models and MLOps practices.
- 2+ years of experience in data engineering.
- Proficiency in Python, coupled with hands-on experience in ML frameworks such as Tensorflow, Scikit-Learn, and PyTorch.
- Expertise in designing scalable data and ML pipelines.
- Experience in managing ML infrastructure.
- Hands-on experience with Docker, Kubernetes, and Helm.
- Hands-on experience with SQL/No-SQL
- Hands-on experience with AWS/Azure Data/ML-related services.
- Hands-on experience with Flask/FastAPI/Django REST services.
- Thorough understanding of distributed systems and design patterns.
- Proficiency in tools like MLFlow, DVC, Kubeflow, and Airflow.
- Experience in startup environments.
- Experience as Machine Learning Engineer or Architect.
- Experience in System Design.
- Experience in Platform Engineering and Related Concepts.
Our Commitment to Inclusivity and Diversity
At G2, we are committed to creating an inclusive and diverse environment where people of every background can thrive and feel welcome. We consider applicants without regard to race, color, creed, religion, national origin, genetic information, gender identity or expression, sexual orientation, pregnancy, age, or marital, veteran, or physical or mental disability status.
Learn more about our commitments hereCommitments
