Job
Description
What is Blend Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com. What is the Role We are seeking a highly skilled MLOps Engineer with an overall experience 5 years with 3 years as ML Engineer particularly in building and managing ML pipelines in AWS. The ideal candidate has successfully built and deployed at least two MLOps projects using Amazon SageMaker or similar services, with a strong foundation in infrastructure as code and a keen understanding of MLOps best practices. What you’ll be doing? Maintain and enhance existing ML pipelines in AWS with a focus on Infrastructure as Code using CloudFormation. Implement minimal but essential pipeline extensions to support ongoing data science workstreams. Document infrastructure usage, architecture, and design using tools like Confluence, GitHub Wikis, and system diagrams. Act as the internal infrastructure expert, collaborating with data scientists to guide and support model deployments. Research and implement optimization strategies for ML workflows and infrastructure. Work independently and collaboratively with cross-functional teams to support ML product What do we need from you? 5+ years of hands-on DevOps experience with AWS Cloud. Proven experience with at least two MLOps projects deployed using SageMaker or similar AWS services. Strong proficiency in AWS services: SageMaker, ECR, S3, Lambda, Step Functions. Expertise in Infrastructure as Code using CloudFormation for dev/test/prod environments. Solid understanding of MLOps best practices and Data Science principles. Proficient in Python for scripting and automation. Experience building and managing Docker images. Hands-on experience with Git-based version control systems such as AWS CodeCommit or GitHub, including GitHub Actions for CI/CD pipelines. What do you get in return? Competitive Salary : Your skills and contributions are highly valued here, and we make sure your salary reflects that, rewarding you fairly for the knowledge and experience you bring to the table. Dynamic Career Growth : Our vibrant environment offers you the opportunity to grow rapidly, providing the right tools, mentorship, and experiences to fast-track your career. Idea Tanks : Innovation lives here. Our "Idea Tanks" are your playground to pitch, experiment, and collaborate on ideas that can shape the future. Growth Chats : Dive into our casual "Growth Chats" where you can learn from the best whether it's over lunch or during a laid-back session with peers, it's the perfect space to grow your skills. Snack Zone : Stay fueled and inspired! In our Snack Zone, you'll find a variety of snacks to keep your energy high and ideas flowing. Recognition & Rewards : We believe great work deserves to be recognized. Expect regular Hive-Fives, shoutouts and the chance to see your ideas come to life as part of our reward program. Fuel Your Growth Journey with Certifications : We’re all about your growth groove! Level up your skills with our support as we cover the cost of your certifications. Show more Show less
