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Senior Staff Machine Learning Engineer
Tekion
posted 23d ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
- Execute the RD and product roadmap based on industry insights and business needs.
- Collaborate with stakeholders to align ML solutions with business objectives.
- Develop robust APIs and microservices for seamless ML model integration into production systems.
- Build feature pipelines for model serving and ensure effective integration with front-end applications, databases, and back-end services.
- Mentor and guide machine learning engineers, fostering team growth through training and collaboration.
- Conduct code reviews to maintain quality and adhere to best practices.
- Manage end-to-end MLOps pipelines for data collection, model training, validation, and monitoring.
- Ensure adherence to version control, testing, and model governance best practices.
- Implement model compression, quantization, and distributed training techniques.
- Track key metrics and optimize models post-deployment.
- Work with cloud architects and DevOps to design scalable ML infrastructure.
- Oversee deployment and management of compute and storage resources for model training and inference.
- Collaborate with applied scientists and analysts to convert model requirements into production-ready solutions.
- Establish monitoring and alerting systems for deployed models to ensure prompt issue resolution.
- Create and maintain documentation for ML architecture and best practices.
- Stay current with ML technologies and contribute to ongoing enhancement efforts.
Required Qualifications
- Bachelors/ Masters / PhD in Computer Science or related field.
- 9+ years of hands-on experience as a Machine Learning Engineer or Architect with a strong portfolio of deployed ML models for batch, streaming and realtime usecases
- Proficient in Python for model development and data manipulation, and experience with Java or Scala for building production systems.
- Familiarity with messaging queues (e.g., Kafka, SQS) and MLOps tools (e.g., MLflow, Kubeflow, Airflow).
- Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization (Docker, Kubernetes).
- Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and data stores (e.g., Elasticsearch, MongoDB, PostgreSQL).
- Knowledge of data processing and ETL tools (e.g., Apache Spark, Kafka).
- Experience in monitoring tools Grafana and Prometheus
- Strong problem-solving skills and analytical mindset.
Preferred Qualifications
- Experience in large-scale production systems and distributed computing.
- Contributions to open-source projects or active participation in the ML community.
- Demonstrated leadership capabilities and experience in mentoring junior engineers.
- Innovative mindset with a track record of developing solutions leading to significant business improvements or patents.
- A collaborative approach to working across multiple products and application teams.
- A willingness to learn, share, and improve continuously.Perks and Benefits
- Competitive compensation
- Generous stock options
- Medical Insurance coverage
- Work with some of the brightest minds from Silicon Valley s most dominant and successful companie
Employment Type: Full Time, Permanent
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People are getting interviews at Tekion through
People are getting interviews through
(based on 55 Tekion interviews)
Referral
Job Portal
Campus Placement
Walkin
Recruitment Consultant
34%
25%
15%
2%
2%
22% candidates got the interview through other sources.
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What people at Tekion are saying
Machine Learning Engineer salary at Tekion
reported by
4
employees
with 3-5
years exp.
₹18
L/yr - ₹27.5
L/yr
119%
more
than the average Machine Learning Engineer Salary in India
View more details
What Tekion employees are saying about work life
based on 292 employees
Flexible timing
Monday to Friday
No travel
Day Shift
Tekion Benefits
Submitted by Company
Silicon Valley Startup Environment Focus on Work / Life Balance Employer Paid Medical/Accident Insurance Remote Positions Available Recognition Culture
Submitted by Employees
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