Sr Machine Learning Engineer
2 days ago
Senior Machine Learning Engineer
About the Role:
We are looking for a Senior Machine Learning Engineer who can take complex machine learning models and make them work in real-world production environments. This role is ideal for someone who not only has deep expertise in machine learning but also understands the challenges of deployment, scalability, and performance optimization across different platforms.
Beyond technical skills, we need someone who can lead a team of MLEs, design end-to-end ML solutions, and effectively communicate technical concepts to both engineers and business stakeholders. If you enjoy solving hard problems, working with cutting-edge ML technologies, and taking ownership of projects from idea to deployment, this role is for you.
What You'll Be Doing:
Building and Deploying ML Models
- Design, build, optimize, deploy and monitor machine learning models for production use cases.
- Ensure scalability, reliability, and efficiency of ML pipelines across cloud and on-prem environments.
- Work with data engineers to design data pipelines that feed into ML models.
- Optimize model performance, ensuring low latency and high accuracy.
Leading and Architecting ML Solutions
- Lead a team of ML Engineers, providing technical mentorship and guidance.
- Architect ML solutions that integrate seamlessly with business applications.
- Ensure models are explainable, auditable, and aligned with business goals.
- Drive best practices in MLOps, CI/CD, and model monitoring.
Collaborating and Communicating
- Work closely with business stakeholders to understand problem statements and define ML-driven solutions.
- Collaborate with software engineers, data engineers, platform engineers and product managers to integrate ML models into production systems.
- Present technical concepts to non-technical stakeholders in an easy-to-understand manner.
What We're Looking For:
Machine Learning Expertise
- Deep understanding of supervised and unsupervised learning, deep learning, and NLP techniques
,
and large language models (LLMs). - Experience in training, fine-tuning, and deploying ML
and LLM
models at scale. - Proficiency in ML frameworks such as TensorFlow, PyTorch, Scikit-learn etc.
Production and Cloud Deployment
- Hands-on experience deploying models to AWS, GCP, or Azure.
- Understanding of MLOps, including CI/CD for ML models, model monitoring, and retraining pipelines.
- Experience working with Docker, Kubernetes, or serverless architectures is a plus.
Data Handling
- Strong programming skills in Python.
- Proficiency in SQL and working with large-scale datasets.
- Familiarity with distributed computing frameworks like Spark or Dask is a plus.
Leadership and Communication
- Ability to lead and mentor a team of ML Engineers and collaborate effectively across functions.
- Strong communication skills to explain technical concepts to business teams.
- Passion for staying updated with the latest advancements in ML and AI.
Experience Needed:
- 6+ years of experience in machine learning engineering or related roles.
- Experience in deploying and managing ML and LLM models in production.
- Proven track record of working in cross-functional teams and leading ML projects.
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