8 часов назад
Software Engineer II (Machine Learning)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer II (Machine Learning): Developing large-scale data pipelines and deep learning systems with an accent on sequence and time-series modeling, agentic workflows, and production MLOps. Focus on training, evaluating, optimizing, and monitoring machine learning models in production.
Location: Gurgaon, India; hybrid working opportunities
Company
is a quantitative trading firm developing electronic trading infrastructure and supporting independent trading teams with market access, data, compute, research infrastructure, risk management, and business services.
What you will do
- Develop data pipelines for collecting, processing, and analyzing diverse datasets at scale.
- Design and implement deep learning architectures for large-volume data processing.
- Conduct experiments and tests to evaluate model performance and identify improvements.
- Build and manage agentic workflows for scalable AI and machine learning solutions.
- Fine-tune machine learning models and build pipelines for monitoring and continuously improving production models.
Requirements
- Bachelor’s, master’s, or PhD degree in computer science or a related field.
- 2–6 years of relevant experience.
- Experience training, building, and deploying large-scale deep learning models.
- Experience designing and implementing sequence and time-series models.
- Expertise in Python and hands-on experience with PyTorch or TensorFlow.
- Experience with Git, CI/CD pipelines, MLOps, Linux, SQL, and Bash scripting.
Culture & Benefits
- Collaborative, welcoming, and results-oriented working environment with minimal hierarchy.
- Generous paid time off policies.
- Savings plans and financial wellness tools available by region.
- Breakfast, lunch, and snacks provided daily.
- Wellness experiences, fitness reimbursements, sports teams, and company events.
- Volunteer opportunities, charitable giving, workshops, and continuous learning opportunities.
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