Senior Machine Learning Engineer

Harness is a high-growth company that is disrupting the software delivery market. Our mission is to enable the 30 million software developers in the world to deliver code to their users reliably, efficiently, securely and quickly, increasing customers’ pace of innovation while improving the developer experience. We offer solutions for every step of the software delivery lifecycle to build, test, secure, deploy and manage reliability, feature flags and cloud costs. The Harness Software Delivery Platform includes modules for CI, CD, Cloud Cost Management, Feature Flags, Service Reliability Management, Security Testing Orchestration, Chaos Engineering, Software Engineering Insights and continues to expand at an incredibly fast pace.   Harness is led by technologist and entrepreneur Jyoti Bansal, who founded AppDynamics and sold it to Cisco for $3.7B. We’re backed with $425M in venture financing from top-tier VC and strategic firms, including J.P. Morgan, Capital One Ventures, Citi Ventures, ServiceNow, Splunk Ventures, Norwest Venture Partners, Adage Capital Partners, Balyasny Asset Management, Gaingels, Harmonic Growth Partners, Menlo Ventures, IVP, Unusual Ventures, GV (formerly Google Ventures), Alkeon Capital, Battery Ventures, Sorenson Capital, Thomvest Ventures and Silicon Valley Bank. Job Summary:
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.

Requirements :
• 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.   Technical Skills:
• Programming: Proficiency in Python and familiarity with ML libraries (e.g.,
TensorFlow, 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 in the news:

• Harness Grabs a $150m Line of Credit
• Welcome Split!
• SF Business Times - 2024 - 100 Fastest-Growing Private Companies in the Bay Area
• Forbes - 2024 America's Best Startup Employers
• SF Business Times - 2024 Fastest Growing Private Companies Awards
• Fast Co - 2024 100 Best Workplaces for Innovators

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 security@harness.io. 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.