Senior Machine Learning Engineer

Spectraforce Technologies; Newark (NJ); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Spectraforce Technologies seeks a Senior Machine Learning Engineer focused on Generative AI to deploy and operate GenAI workloads in production. You will bridge theory and practice, building reliable pipelines, secure models, and cost-efficient infrastructure across cloud and on-prem environments.

The role emphasizes model deployment, data engineering, and DevOps maturity, requiring strong Python skills and GenAI expertise within a fast-paced, hybrid Newark setting.

Qualifications

• Bachelor's degree in computer science or related field; master's preferred.
• 5+ years of production ML engineering experience.
• Strong Python and software engineering fundamentals.
• Solid ML fundamentals and lifecycle management.
• Experience with cloud, containers, and infra management.
• Familiar with DevOps and automation tools.
• GenAI frameworks, prompt engineering, model serving expertise.
• Ability to manage GPU/TPU resources and optimize serving.
• Experience building agentic and multi-agent systems.
• Proven cost optimization track record in AI deployments.
• Comfortable in fast-paced, independent work environments.

Responsibilities

• Model deployment, monitoring, and maintenance in production.
• Build and maintain data pipelines and storage for model ops.
• Leverage cloud platforms and container orchestration for deployments.
• Develop CI/CD pipelines and automate deployment processes.
• Implement secure coding, auth, and robust monitoring/alerting.
• Apply GenAI expertise across LLMs, architectures, and tools.
• Utilize RAG and human-in-the-loop techniques where appropriate.
• Develop agent and multi-agent systems with LangChain and APIs.
• Identify and execute cost optimization for GenAI deployments.

Skills

Python proficiency

Software engineering

GenAI frameworks

Prompt engineering

Independent worker

Education

Bachelor's degree in CS/Engineering or related

Master's degree preferred

Tools

Docker

Kubernetes

Terraform/CloudFormation

Git

LangChain

Hugging Face

Job description

Title: Senior Machine Learning Engineer (Generative AI Focus)
Duration: 3 months (right to hire)
Location: Newark, NJ (Hybrid)

Interview Process: 3 interview rounds (intro, coding, architecture)

Position Overview:

We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our dynamic team. In the rapidly evolving world of Generative AI (GenAI), this role demands not only traditional machine learning expertise but also a deep understanding of GenAI-specific challenges. The ideal candidate will be a pivotal bridge between the theoretical capabilities of GenAI models and their practical application in production environments. We are looking for someone who can ensure our GenAI solutions are innovative, reliable, scalable, secure, and cost-effective.

Key Responsibilities:

Model Deployment & Maintenance: Focus on deploying, monitoring, and maintaining GenAI models in production, ensuring they function reliably in real-world settings.

Data Engineering: Build and maintain efficient data pipelines and storage solutions that support model operations.

Infrastructure Management: Utilize cloud platforms (AWS, Azure, GCP) for model deployment, containerization (Docker), orchestration (Kubernetes), and infrastructure as code (Terraform/CloudFormation).

DevOps & Automation: Develop CI/CD pipelines, manage version control (Git), and automate deployment processes for seamless operational efficiency.

Security & Monitoring: Implement secure coding practices, authentication, authorization, and set up robust monitoring and alerting systems for both infrastructure and model performance.

Generative AI Expertise: Deep understanding of LLMs, GenAI architectures, frameworks like Hugging Face, prompt engineering, and specialized infrastructure for GenAI workloads.

Advanced Techniques: Apply advanced GenAI techniques like Retrieval-Augmented Generation (RAG), hallucination monitoring, and human-in-the-loop systems.

Agent Development: Design and develop agent and multi-agent systems using frameworks like LangChain, enabling them to interact with external APIs and tools efficiently.

Cost Optimization: Implement strategies to manage and reduce the operational costs associated with GenAI deployments.

Qualifications:

• Bachelor's degree in computer science/Engineering, data science, or a related field. Master's degree preferred
• At least five plus years' experience as a machine learning engineer, deploying models in production
• Strong proficiency in Python and software engineering principles.
• Solid understanding of machine learning fundamentals and model lifecycle management.
• Experience with cloud platforms, containerization, and infrastructure management.
• Familiarity with DevOps practices and automation tools.
• Expertise in GenAI frameworks, prompt engineering, and model serving.
• Ability to manage GPU/TPU resources and optimize model serving frameworks.
• Experience in developing agentic systems and multi-agent architectures.
• Proven track record in cost optimization in AI deployments.
• Experience working in fast paced environment and independent worker

Impact & Purpose:

• We are committed to attracting the best and brightest talent who are driven by impact and purpose.
• The Senior Machine Learning Engineer will play a crucial role in advancing our GenAI capabilities, pushing the boundaries of innovation while ensuring practical application and scalability.
• If you are passionate about transforming theoretical AI models into impactful real-world solutions, we invite you to join our team.