As a Senior Machine Learning Engineer at Traceable, you will be instrumental in transforming ML models from prototype to production at scale. You will work closely with data scientists, MLOps engineers, and product teams to design, develop and deploy critical, high-performing ML solutions. This role requires a blend of engineering, MLOps, and data science skills to streamline model deployment and ensure continuous, reliable operations in the production environments.
Responsibilities
- Model Productionization: Convert ML models from prototypes to scalable, production-ready solutions. Optimize models for performance, scalability, and resource efficiency.
- Integration and Deployment: Develop and maintain enablement pipelines for continuous integration and deployment of ML models, ensuring smooth transitions from development to production.
- Scalability and Optimization: Implement distributed systems and leverage cloud-based architectures (e.g., AWS, GCP) to scale ML models and optimize for low latency and high availability.
- Model Monitoring and Maintenance: Set up monitoring systems to track model performance in production, detect data drift, and trigger automated retraining when needed
- Innovation and Tooling: Evaluate and integrate new tools, frameworks, and libraries that can improve model deployment speed and robustness and keep Traceable.ai at the cutting edge of ML infrastructure.
- Documentation and Knowledge Sharing: Document processes, maintain well-structured codebases, promote best practices in ML engineering, and lead internal knowledge-sharing sessions to foster a culture of continuous improvement and technical excellence.
- Education: Bachelor’s or master’s degree in computer science, Machine Learning, Engineering, or a related field.
- Experience: 5+ years in machine learning engineering or software engineering with significant ML focus, including experience in deploying ML models in production.
- Programming: Proficiency in Python and familiarity with ML libraries (e.g.,sensorFlow, PyTorch, Scikit-Learn).
- MLOps Tools: Experience with CI/CD for ML, containerization (Docker, Kubernetes), and workflow orchestration tools (e.g., Airflow, MLflow).
- Cloud Infrastructure: Strong knowledge of cloud platforms (AWS or GCP), including managed ML services (SageMaker, Vertex AI).
- Data Processing: Familiarity with distributed computing frameworks (e.g., Spark, Dask) and data pipelines. Experience with relational databases like MySQL, PostgreSQL and experience with SQL query tuning, performance optimizations is a plus.
- Problem-Solving: Proven ability to troubleshoot and optimize ML systems in production.
- Collaboration: Excellent communication and teamwork skills, with experience working in.
- Adaptability: Ability to thrive in a fast-paced, evolving environment and rapidly adopt new tools and technologies.
Work Location
- Bangalore. The successful candidate will be expected to be in the Bangalore office 3x/ week.
What You Will Have at Harness
- Experience building a transformative product
- End-to-end ownership of your projects
- Competitive salary
- Comprehensive healthcare benefit
- Flexible work schedule
- Quarterly Harness TGIF-Off / 4 days
- Paid Time Off and Parental Leave
- Monthly, quarterly, and annual social and team building events
- Monthly internet reimbursement
- Harness AI Tackles Software Development’s Real Bottleneck
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- Jyoti Bansal, Harness | theCUBEd Awards
- Eight years after selling AppDynamics to Cisco, Jyoti Bansal is pursuing an unusual merger
- Harness snags Split.io, as it goes all in on feature flags and experiments
- Exclusive: Jyoti Bansal-led Harness has raised $150 million in debt financing
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex or national origin.
Note on Fraudulent Recruiting/Offers
We have become aware that there may be fraudulent recruiting attempts being made by people posing as representatives of Harness. These scams may involve fake job postings, unsolicited emails, or messages claiming to be from our recruiters or hiring managers.
Please note, we do not ask for sensitive or financial information via chat, text, or social media, and any email communications will come from the domain @harness.io. Additionally, Harness will never ask for any payment, fee to be paid, or purchases to be made by a job applicant. All applicants are encouraged to apply directly to our open jobs via our website. Interviews are generally conducted via Zoom video conference unless the candidate requests other accommodations.
If you believe that you have been the target of an interview/offer scam by someone posing as a representative of Harness, please do not provide any personal or financial information and contact us immediately at [email protected]. You can also find additional information about this type of scam and report any fraudulent employment offers via the Federal Trade Commission’s website (https://consumer.ftc.gov/articles/job-scams), or you can contact your local law enforcement agency.
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What We Do
Harness is a leader in AI-native software delivery, dedicated to empowering developers and engineering teams worldwide. We revolutionize how software is built, tested, deployed, and optimized by driving efficiency, reliability, and speed throughout the software development lifecycle. At Harness, we envision a world where developers focus on innovation, free from repetitive tasks, supported by tools that streamline every step.
Our platform leverages AI and automation across all key pillars of software delivery: Continuous Integration, Continuous Delivery, Feature Flags and Experimentation, Cloud Cost Management, Security Testing, and more. By automating traditionally manual processes that slow down engineering teams, Harness enables organizations to release software faster, reduce errors, and optimize costs—all while enhancing the developer experience and flexibility.
Harness is transforming software delivery on a global scale. As a pioneer in AI-driven automation, we streamline complex development processes, eliminate inefficiencies, and empower developers to innovate freely. Our mission is ambitious: enabling millions of developers to deliver code faster, more reliably, and with greater ease than ever before.
Why Work With Us
Harness is built on a culture of growth, collaboration, and transparency, where team members are encouraged to push boundaries and solve meaningful challenges. We invest in personal and professional development, value work-life balance, and foster a supportive environment—making Harness an ideal place to make a real impact in tech.
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