Senior Machine Learning Operations Engineer
Uplers
Bengaluru, Karnataka, IndiaSENIOR
RemoteAIMLDevOps
Job Description
Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle.
Responsibilities
- Automate the deployment and retraining of ML models.
- Monitor health and performance of production ML models.
- Provide architectural guidance and mentorship.
Qualifications
- Salary: Confidential (based on experience)
- Shift: (GMT+05:30) Asia/Kolkata (IST)
- Opportunity Type: Office (Bengaluru)
- Placement Type: Full time Permanent Position
- (*Note: This is a requirement for one of Uplers' client - Smartsheet)
- What do you need for this opportunity?
- Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices.
- Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models.
- Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models.
- Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards.
- Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation.
- Incorporate user feedback for iterative improvements and manage necessary model retraining cycles.
- Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them).
- Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet.
- Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC).
- Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers.
- Distill complex ML concepts into easy-to-follow technical documentation.
- 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines.
- 7+ years of programming experience in languages used in AI/ML (eg python, scala etc)
- 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc.
- Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms.
- Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs).
- A degree in Computer Science, Engineering, or a related field or equivalent practical experience.
- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
Nice to have
- Experience with Generative AI approaches.
- Familiarity with AI security practices.