Principal Machine Learning Engineer

Machine Learning EngineerMachine Learning EngineerFull TimeRemoteTeam 51-200H1B SponsorCompany Site LinkedIn

Location

United States

Posted

49 days ago

Salary

Not specified

Bachelor Degree5 yrs expExperience acceptedEnglishAWSAzureGoogle Cloud PlatformKubernetesPythonPy TorchScikit LearnSparkSQLTensorflowTerraform

Job Description

• Define high-level business objectives directly with clients, then develop and execute the project plan to meet those objectives • Proactively research and apply knowledge within the data science space to deliver best-in-class solutions • Lead both small and large teams over the entire data science lifecycle – from problem definition to model automation and deployment • Provide technical leadership to guide development work across teams while also owning and delivering specific technical components yourself • Manage all aspects of client relationships and create value-driving initiatives for the company • Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights • Write code in SQL, Python, and Spark following software engineering best practices

Job Requirements

Degree in Computer Science, Engineering, Mathematics, or equivalent experience
5+ years of experience developing and deploying ML models in any platform (Azure, AWS, GCP, Databricks, etc.)
Experience designing, deploying, and scaling Generative AI and machine learning systems in production, including LLM/Model serving, orchestration, and GPU resource management on Kubernetes for high-volume, business-critical applications
Experience with managing stakeholders and collaborating with customers
Strong written and verbal communication skills required
Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc.
Experience with deep learning frameworks like TensorFlow or PyTorch
Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time and batch processing
Experience with CI/CD pipelines (e.g., DevOps pipelines, GitHub Actions)
Knowledge of infrastructure as code (e.g., Terraform, ARM Template, Databricks Asset Bundles)
Understanding of advanced machine learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling
Experience with generative AI and LLMs, such as LLamaIndex and LangChain
Deep expertise in Generative AI and Large Language Models, with a strong focus on optimizing GenAI applications for performance, cost, and reliability
Familiarity with Agile methodologies, preferably Scrum.