Sr ML Engineer

dicedemo; Boston (AL); On-site; USD 130,000 - 190,000; Full time

Job summary

dicedemo is seeking a Senior Machine Learning Engineer to design, build, deploy, and scale machine learning solutions that solve complex business problems. This role sits at the intersection of ML, software engineering, data, and AI, taking models from experimentation through production, and requires strong ML expertise paired with robust software practices.

You will design end-to-end ML pipelines, develop solutions using supervised and unsupervised learning, deep learning, NLP, and Generative

Qualifications

• 5+ years of professional experience in Machine Learning Engineering, Software Engineering, Data Science, or a related technical field
• Strong programming experience with Python
• Demonstrated experience developing and deploying machine learning models into production
• Strong knowledge of machine learning algorithms, statistics, model evaluation, and feature engineering
• Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Experience building scalable production software and APIs
• Experience with AWS, Azure, and/or GCP
• Strong understanding of data structures, algorithms, software engineering principles, and distributed systems
• Experience with SQL and large-scale data processing
• Experience with containerization and deployment technologies such as Docker and Kubernetes
• Strong communication skills and ability to collaborate across engineering, data, and product teams

Responsibilities

• Design, develop, and deploy machine learning models and AI-powered applications into production
• Build end-to-end ML pipelines covering data preparation, feature engineering, model training, evaluation, deployment, and monitoring
• Develop solutions using supervised and unsupervised learning, deep learning, NLP, recommendation systems, and/or Generative AI
• Build and optimize applications leveraging Large Language Models (LLMs)
• Develop solutions involving RAG, embeddings, vector search, fine-tuning, and prompt/model optimization
• Train, evaluate, fine-tune, and optimize machine learning models
• Develop production-quality software primarily using Python
• Work with ML frameworks such as PyTorch, TensorFlow, scikit-learn, or JAX
• Deploy and operate models in cloud environments such as AWS, Azure, or GCP
• Build scalable APIs and services for real-time and batch model inference
• Partner with Data Scientists, Data Engineers, Software Engineers, and Product teams to translate business problems into ML solutions
• Establish model evaluation, testing, monitoring, and performance standards
• Improve model accuracy, latency, scalability, reliability, and cost efficiency
• Mentor engineers and contribute to ML engineering standards, architecture, and best practices
• Evaluate emerging AI/ML technologies and determine where they can provide meaningful business value

Skills

Python

ML Engineering

Production ML

Distributed systems

SQL

Cloud

APIs

Docker

Kubernetes

Communication

Tools

PyTorch

TensorFlow

scikit-learn

JAX

Hugging Face

LangChain

LlamaIndex

OpenAI APIs

MLflow

Kubeflow

SageMaker

Vertex AI

CUDA

Job description

Senior Machine Learning Engineer

Position Overview

We are seeking aSenior Machine Learning Engineer to design, build, deploy, and scale machine learning solutions that solve complex business and technical problems.

This role will work at the intersection ofmachine learning, software engineering, data, and artificial intelligence, taking models from experimentation through production. The ideal candidate combines strong ML expertise with excellent software engineering skills and experience building reliable, scalable production systems.

Key Responsibilities

• Design, develop, and deploymachine learning models and AI-powered applications into production
• Build end-to-end ML pipelines covering data preparation, feature engineering, model training, evaluation, deployment, and monitoring
• Develop solutions usingsupervised and unsupervised learning, deep learning, NLP, recommendation systems, and/or Generative AI
• Build and optimize applications leveragingLarge Language Models (LLMs)
• Develop solutions involvingRAG, embeddings, vector search, fine-tuning, and prompt/model optimization
• Train, evaluate, fine-tune, and optimize machine learning models
• Develop production-quality software primarily usingPython
• Work with ML frameworks such asPyTorch, TensorFlow, scikit-learn, or JAX
• Deploy and operate models in cloud environments such asAWS, Azure, or GCP
• Build scalable APIs and services for real-time and batch model inference
• Partner with Data Scientists, Data Engineers, Software Engineers, and Product teams to translate business problems into ML solutions
• Establish model evaluation, testing, monitoring, and performance standards
• Improve model accuracy, latency, scalability, reliability, and cost efficiency
• Mentor engineers and contribute to ML engineering standards, architecture, and best practices
• Evaluate emerging AI/ML technologies and determine where they can provide meaningful business value

Required Qualifications

• 5+ years of professional experience inMachine Learning Engineering, Software Engineering, Data Science, or a related technical field
• Strong programming experience withPython
• Demonstrated experience developing and deploying machine learning models into production
• Strong knowledge of machine learning algorithms, statistics, model evaluation, and feature engineering
• Experience with ML frameworks such asPyTorch, TensorFlow, or scikit-learn
• Experience building scalable production software and APIs
• Experience withAWS, Azure, and/or GCP
• Strong understanding of data structures, algorithms, software engineering principles, and distributed systems
• Experience with SQL and large-scale data processing
• Experience with containerization and deployment technologies such asDocker and Kubernetes
• Strong communication skills and ability to collaborate across engineering, data, and product teams

Preferred Qualifications

• Experience building productionGenerative AI and LLM applications
• Experience withRAG, embeddings, vector databases, prompt engineering, and LLM evaluation
• Experience fine-tuning or adapting foundation models
• Experience withHugging Face, LangChain, LlamaIndex, OpenAI-compatible APIs, or similar AI development frameworks
• Experience with MLOps technologies such asMLflow, Kubeflow, SageMaker, Vertex AI, or Azure Machine Learning
• Experience with distributed computing technologies such asSpark or Ray
• Experience building recommendation, ranking, search, NLP, or computer vision systems
• Experience with model serving and inference optimization
• Familiarity with GPU computing andCUDA
• Experience mentoring junior engineers or providing technical leadership

What Success Looks Like

The Senior Machine Learning Engineer will help turn AI and machine learning concepts intoreliable, scalable, production-ready products. Success means building models that don't simply perform well in experimentation, but deliver measurable business outcomes in production while meeting standards for performance, reliability, scalability, and maintainability.