Software Engineer

General Summary of Position:

Granite seeking a talented and motivated Software Engineer to join our team. The Software Engineer will be responsible for designing, developing, and implementing cutting-edge AI and machine learning solutions that solve complex business problems and improve our products or services. The ideal candidate should have a strong background in machine learning, deep learning, and data analysis, as well as a passion for staying updated on the latest developments in the field

 

The right candidate will be a self-starter, able to work independently or as a team member.  Must be able to thrive in a fast-paced environment and learn new technologies quickly.  This is a growing company where you will be able to have a significant impact on our internal processes and get a chance to add directly to the goals of the organization.

 

Duties and Responsibilities: 

  Data Collection & Preparation 

• Gather and preprocess multimodal data for AI/ML models, including cleaning, augmentation (e.g., RAG for text enrichment), and synthetic data generation. 
• Implement embedding techniques (e.g., BERT, sentence-transformers) for semantic feature extraction. 

  Model Development 

• Design and deploy AI/ML models, including neural networks (transformers, LLMs), decision trees, and ensemble methods. 
• Specialize in prompt engineering, Model Context Protocol design, and function calling integrations for LLM-based applications. 
• Apply supervised fine-tuning (SFT) for domain-specific adaptation of pre-trained models. 

  Training & Evaluation 

• Optimize models using frameworks like LangChain for context-aware workflows. 
• Evaluate performance with metrics tailored to generative AI (e.g., coherence, retrieval accuracy). 

  Feature Engineering 

• Leverage embeddings and attention mechanisms to enhance model interpretability and efficiency. 

  Model Deployment 

• Deploy scalable, servable AI applications on GCP using Vertex AI, Cloud Run, or Kubernetes. 
• Implement Model Guard frameworks for output validation, bias mitigation, and ethical compliance. 

  Continuous Learning 

• Stay updated on advancements in LLMs, RAG architectures, and emerging tools (e.g., LangChain, LlamaIndex). 

  Collaboration 

• Partner with cross-functional teams to align AI solutions (e.g., function calling, Model Context Protocol) with business use cases. 

  Documentation 

• Detail prompt templates, RAG pipelines, and fine-tuning procedures for reproducibility. 

  Security & Privacy 

• Ensure compliance with data governance standards in AI workflows (e.g., anonymization in embeddings, Model Guard audits).

Required Qualifications:

 

  Education 

• Master’s or Bachelor’s degree (or higher) in computer science, data science, artificial intelligence, machine learning, or a closely related field. 

  Deep Learning Expertise 

• Proficiency in deep learning frameworks such as TensorFlow and PyTorch, with hands-on experience in neural network architectures including CNNs, RNNs, and advanced transformer models (e.g., BERT, GPT). 
• Experience with retrieval-augmented generation (RAG) systems and prompt engineering for LLMs. 

  Model Optimization 

• Demonstrated ability to optimize AI/ML models for performance, scalability, and efficiency, including techniques such as quantization, pruning, and leveraging GPU/CPU acceleration (CUDA, mixed-precision training).  
• Familiarity with ethical AI frameworks and model guardrails. 

  Hyperparameter Tuning 

• Experience with hyperparameter optimization and supervised fine-tuning (SFT) of large language models and neural networks. 

  Programming & Frameworks 

• Strong programming skills in Python, with proficiency in libraries and frameworks such as Hugging Face Transformers, LangChain, PyTorch, TensorFlow, and spaCy. 
• Experience with function calling, embeddings, and context management protocols in AI applications. 

  Natural Language Processing (NLP) 

• Expertise in NLP tasks such as text classification, semantic search, entity recognition, and language modeling using advanced transformer-based models and embeddings. 

  MLOps & Deployment 

• Hands-on experience with MLOps practices, including model versioning, CI/CD, and automated deployment using tools such as MLflow, Kubeflow, or GCP Vertex AI. 
• Proficiency in deploying scalable AI applications on cloud platforms (GCP, AWS, or Azure), with emphasis on GCP tools like Vertex AI and Cloud Run. 
• Experience deploying open-source AI models using Ollama for local and server-based inference, including Docker containerization and cloud VM configurations (AWS EC2, GCP Compute Engine). 
• Familiarity with Ollama model serving workflows: model pulling and version management, API endpoint configuration, secure remote access, and performance optimization for CPU/GPU environments. 
• Experience with container orchestration (Docker, Kubernetes) for AI model serving, including Ollama-based services. 

  Big Data & Distributed Computing 

• Understanding of distributed training and serving of large-scale AI models. 
• Familiarity with big data processing is a plus, but primary focus is on scalable AI/ML model deployment and inference. 

  Automated Machine Learning (AutoML) 

• Experience with AutoML tools and platforms for automating model selection, training, and hyperparameter tuning (e.g., GCP Vertex AI AutoML). 

  Testing & Debugging 

• Proficiency in testing, validating, and debugging AI/ML models, with a focus on model performance, reliability, and fairness (including bias detection and model guard integration). 

  Security & Privacy 

• Implementing security best practices for AI model APIs, including firewall rules and SSH access controls for Ollama endpoints and cloud deployments. 

Preferred Qualifications:

• Advanced degrees in AI/ML-related fields.
• Experience in natural language processing, computer vision, or other specialized AI/ML domains.

 

Qualifications

Granite delivers advanced communications and technology solutions to businesses and government agencies throughout the United States and Canada. We provide exceptional customized service with an emphasis on reliability and outstanding customer support and our customers include over 85 of the Fortune 100. Granite has over $1.85 Billion in revenue with more than 2,100 employees and is headquartered in Quincy, MA. Our mission is to be the leading telecommunications company wherever we offer services as well as provide an environment where the value of each individual is recognized and where each person has the opportunity to further their growth and achieve success.

Granite has been recognized by the Boston Business Journal as one of the "Healthiest Companies" in Massachusetts for the past 15 consecutive years.

Our offices have onsite fully equipped state of the art gyms for employees at zero cost.

Granite's philanthropy is unparalleled with over $300 million in donations to organizations such as Dana Farber Cancer Institute, The ALS Foundation and the Alzheimer's Association to name a few.

We have been consistently rated a "Fastest Growing Company" by Inc. Magazine.

Granite was named to Forbes List of America's Best Employers 2022, 2023 and 2024.

Granite was recently named One of Forbes Best Employers for Diversity.

Our company's insurance package includes health, dental, vision, life, disability coverage, 401K retirement with company match, childcare benefits, tuition assistance, and more.

If you are a highly motivated individual who wants to grow your career with a fast paced and progressive company, Granite has countless opportunities for you.

EOE/M/F/Vets/Disabled