Senior Machine Learning Engineer
Senior Machine Learning Engineer
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
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.
performance in production detect data drift and trigger automated retraining when
needed
can improve model deployment speed and robustness and keep 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: Bachelors or masters 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.
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 TimesFastest-Growing Private Companies in the Bay Area
- Forbes - 2024 Americas Best Startup Employers
- SF Business Times - 2024 Fastest Growing Private Companies Awards
- Fast Co -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 @. 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. You can also find additional information about this type of scam and report any fraudulent employment offers via the Federal Trade Commissions website ( or you can contact your local law enforcement agency.
Required Experience:
Senior IC
Employment Type
Full Time
