Aimpoint DigitalRemote
Principal Machine Learning Engineer 2026 - US, UK
United States
Full Time
3 hours ago
H1B Sponsor Likely
Key skills
PythonSQLAIMachine LearningMLDeep LearningNatural Language ProcessingComputer VisionGenerative AIGenAILLMLarge Language ModelsLangChainLlamaIndexPyTorchTensorFlowMLOpsXGBoostData EngineeringAnalyticsDatabricksSparkFastAPIAWSAzureGCPTerraformKubernetesGitHub ActionsAzure FunctionsGitHubAgileScrumCI/CDLeadershipCommunication
About this role
Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This role focuses on enabling clients to extract insights from their data using machine learning and statistical modeling while providing technical leadership and managing client relationships.
Responsibilities:
- 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
Requirements:
- Degree in Computer Science, Engineering, Mathematics, or equivalent experience
- 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
- Ability to manage an individual workstream independently
- 5+ years of experience developing and deploying ML models in any platform (Azure, AWS, GCP, Databricks etc.)
- Ability to apply data science methodologies and principles to real life projects
- Expertise in software engineering concepts and best practices
- Self-starter with excellent communication skills, able to work independently, and lead projects, initiatives, and/or people
- Willingness to travel
- 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
- Understanding of MLOps or LLMOps
- Consulting Experience
- 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