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- Tasks: Develop and manage ML models using AWS SageMaker and build scalable solutions.
- Company: Derisk360 transforms businesses with AI expertise and deep domain knowledge.
- Benefits: Enjoy a competitive salary, performance bonuses, and opportunities for growth in a tech-forward environment.
- Why this job: Lead innovative ML projects and collaborate with top-tier clients in a high-impact, AI-focused team.
- Qualifications: 7+ years in software engineering, 3+ years with AWS SageMaker, and strong Python skills required.
- Other info: Work in Bangalore, Chennai, or Gurugram with access to complex cloud-native platforms.
The predicted salary is between 48000 - 72000 £ per year.
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We’re Hiring: ML Data Engineer
Experience: 7+ Years
Location: Bangalore / Chennai / Gurugram
Company: Derisk360
Are you passionate about building scalable ML pipelines and deploying intelligent systems in the cloud? At Derisk360, we help transform businesses by combining AI expertise with deep domain knowledge. We\’re seeking a Senior ML Engineer to take our ML infrastructure to the next level using AWS SageMaker and state-of-the-art MLOps practices.
What You’ll Do
- Develop, deploy, and manage ML models using AWS SageMaker, including pipelines, real-time endpoints, and batch transform jobs.
- Architect infrastructure using Infrastructure as Code (IAC) tools such as Terraform or AWS CloudFormation.
- Build robust, scalable solutions across real-time and batch systems with high reliability and performance.
- Design secure and scalable AWS networking environments tailored for ML workflows.
- Collaborate with data scientists, ML engineers, and DevOps to optimize model development and deployment pipelines.
- Contribute to automation, CI/CD pipelines, and monitoring strategies for ML systems.
What You Bring
- 7+ years of experience in software engineering, with at least 3+ years working on AWS SageMaker in production environments.
- Proficient in AWS services (EC2, S3, Lambda, IAM, VPC, CloudWatch) and deep understanding of AWS networking concepts.
- Solid experience with Terraform or CloudFormation for IAC implementation.
- Strong programming skills in Python and hands-on experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Familiarity with model training, evaluation, versioning, and operationalizing in cloud environments.
Nice To Have
- Experience integrating ML workflows with data lakes or data pipelines.
- Exposure to MLOps practices including experiment tracking, model registry, and containerization (Docker).
- Understanding of security best practices in AWS for machine learning.
What You’ll Get
- Competitive salary with performance-based bonuses
- Lead innovative ML projects with top-tier insurance and risk-tech clients
- Work in a tech-forward, collaborative environment
- Opportunities to grow within a high-impact, AI-focused team
- Access to complex cloud-native platforms and enterprise-grade ML systems
Seniority level
-
Seniority level
Mid-Senior level
Employment type
-
Employment type
Full-time
Job function
-
Job function
Information Technology
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Industries
Information Services
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ML Data Engineer employer: Derisk360
Contact Detail:
Derisk360 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Data Engineer
✨Tip Number 1
Familiarise yourself with AWS SageMaker and its features. Since the role specifically requires experience with this tool, being able to discuss your hands-on experience and any projects you've completed using SageMaker will set you apart.
✨Tip Number 2
Showcase your knowledge of Infrastructure as Code (IAC) tools like Terraform or CloudFormation. Prepare examples of how you've used these tools in past projects to demonstrate your ability to architect scalable ML solutions.
✨Tip Number 3
Highlight your collaboration skills. The job involves working closely with data scientists and DevOps teams, so be ready to share experiences where you've successfully collaborated on ML projects or optimised deployment pipelines.
✨Tip Number 4
Stay updated on MLOps practices. Understanding concepts like experiment tracking and model registry can give you an edge. Consider discussing any relevant experiences or insights during your conversations with the hiring team.
We think you need these skills to ace ML Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS SageMaker and other relevant AWS services. Emphasise your programming skills in Python and any hands-on experience with ML frameworks like TensorFlow or PyTorch.
Craft a Strong Cover Letter: In your cover letter, express your passion for building scalable ML pipelines and deploying intelligent systems. Mention specific projects where you've successfully implemented MLOps practices or used Infrastructure as Code tools like Terraform.
Showcase Relevant Experience: Detail your 7+ years of software engineering experience, focusing on the 3+ years spent working with AWS SageMaker in production environments. Include examples of how you've collaborated with data scientists and DevOps teams.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops related to machine learning, AWS, or MLOps that you've completed. This shows your commitment to staying updated in the field and can set you apart from other candidates.
How to prepare for a job interview at Derisk360
✨Showcase Your AWS Expertise
Make sure to highlight your experience with AWS services, especially AWS SageMaker. Be prepared to discuss specific projects where you've deployed ML models and how you utilised various AWS tools to optimise performance.
✨Demonstrate Your IAC Skills
Since the role requires knowledge of Infrastructure as Code, be ready to talk about your experience with Terraform or CloudFormation. Share examples of how you've implemented IAC in previous roles to streamline ML workflows.
✨Discuss Collaboration Experience
Collaboration is key in this role. Prepare to discuss how you've worked with data scientists, ML engineers, and DevOps teams in the past. Highlight any successful projects that resulted from effective teamwork.
✨Prepare for Technical Questions
Expect technical questions related to ML frameworks like TensorFlow or PyTorch. Brush up on your programming skills in Python and be ready to solve problems or explain concepts during the interview.
