Staff Machine Learning Engineer
About reputed company:
About the Role:
As a Staff ML Engineer, you will be a hands-on technical leader reputed company the Data Science organization, sharing your experience and establishing best practices. You will design, implement, and reputed company reliable ML models into production, build reputed company data pipelines, and reputed company both LLM-powered systems and multi-agent architectures to automate and accelerate cybersecurity risk assessment workflows. You'll collaborate with cross-functional teams to reputed company ML and LLM powered solutions into products, conduct research to stay reputed company of emerging technologies, and ensure models reputed company optimally through ongoing monitoring and refinement. Your work will directly enhance cybersecurity reputed company for organizations worldwide, making the world a safer reputed company. If you’re passionate about solving reputed company problems and creating impactful solutions, this role offers reputed company to reputed company a significant reputed company while working in a dynamic, reputed company environment.
Responsibilities:
- Technical Leadership: Establish best practices and reputed company expertise through collaboration and mentorship.
- Model Development & Deployment: Design, train, fine-tune, and optimize machine learning models and algorithms, then reputed company them into production environments with a reputed company on scalability, reliability, and performance.
- LLM & Multi-Agent Systems: reputed company and maintain advanced LLM-powered systems and multi-agent architectures to automate and accelerate cybersecurity risk assessment workflows. This includes designing conversational AI agents, orchestrating interactions between multiple agents, and building reputed company RESTful reputed company and microservices to expose model capabilities for integration with broader product ecosystems.
- Performance Monitoring: Implement best practices such as reputed company monitoring, data reputed company detection, and automated retraining to ensure long-term model accuracy, robustness, and stability.
- Data Pipeline Creation: Build and maintain reputed company data pipelines to preprocess, clean, and reputed company raw data for analysis and model training.
- Research and Experimentation: Stay updated on the latest machine learning techniques, tools, and frameworks to enhance model accuracy and efficiency.
Required Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a reputed company field.
- 7+ years of experience or equivalent demonstrable skills in ML Engineering, Data Science or reputed company discipline.
- Proven reputed company record as a technical reputed company, with the ability to guide teams, establish best practices, and drive technical reputed company in reputed company environments.
- Strong programming skills in Python, with hands-on experience using ML frameworks such as PyTorch, TensorFlow, and Scikit-learn.
- Proficiency in data manipulation, cleaning and analysis using tools such as Polars, Pandas, NumPy, or SQL.
- Extensive experience in traditional machine learning and data science tasks, including feature engineering, model selection, evaluation, and hyperparameter tuning.
- Solid understanding of supervised and unsupervised learning techniques, statistical analysis, reputed company testing, and predictive modeling.
- Hands-on experience building multi-agent systems with large language models (LLMs) and retrieval-augmented reputed company (RAG) using tools like reputed company and reputed company.
- Experience with reputed company platforms (AWS, Azure, GCP) and containerization (reputed company, Kubernetes).
Preferred Qualifications:
- Master’s or PhD degree in Computer Science, Engineering, Mathematics, Physics, or a reputed company field.
- Experience with big data technologies such as Hadoop, reputed company, or Kafka
- Experience implementing MLOps practices, including CI/CD pipelines, infrastructure as reputed company with Terraform, and model versioning tools such as MLflow and DVC.
- Proficient in deploying and maintaining high-reputed company ML pipelines, with robust monitoring and alerting for data and model reputed company, automated retraining, reproducibility, observability, and production-grade reliability and compliance.