This page tracks remote ai engineer openings that are location-eligible for New Jersey.
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JRSS is an IT consulting service provider for Government and Fortune 500 clients. As a certified WOSB, SDB, and HUBZone small business, we specialize in Federal Civilian Data, Cloud, and AI/ML enterprise-level solution architecture, design, implementation, and professional staffing. Recognized on the Inc. 5000 list of fastest-growing private companies, we're proud to foster a collaborative culture where innovation and client impact come first.
Role Description JRSS is seeking an AI/ML Engineer. True innovation happens where machine learning meets cloud technology and real-world impact. As an AI/ML Engineer, you'll join a collaborative team of technologists, data scientists, and stakeholders to tackle meaningful challenges using ML, Generative AI, and modern tools. You'll contribute to building and scaling intelligent systems — from core ML models to chatbot and Retrieval-Augmented Generation (RAG) applications. With strong skills in Python, SQL, and cloud platforms like Azure, you'll help deliver practical, forward-looking solutions in dynamic environments. Bring your technical expertise, curiosity, and customer-first mindset to help shape the future of intelligent systems across industries. Core Responsibilities - Design, develop, and deploy scalable machine learning models and AI-driven solutions to address complex business and operational challenges. - Build and enhance Generative AI, LLM, and Retrieval-Augmented Generation (RAG) applications, including chatbot and conversational AI capabilities. - Develop and optimize data pipelines, feature engineering workflows, and large-scale data processing solutions using Python, SQL, and Spark. - Implement and support MLOps practices, including model training, deployment, monitoring, and lifecycle management using tools such as MLflow and Azure cloud services. - Collaborate with cross-functional teams and stakeholders to deliver customer-focused AI/ML solutions while staying current on emerging technologies and industry best practices. Qualifications - 3+ years of experience designing, developing, and deploying machine learning models. - 3+ years of experience with Generative AI, LLMs, or RAG applications. - 4+ years of hands-on experience with Python for ML and data engineering. - Experience with SQL for data manipulation and feature engineering. - Experience with big data tools such as Apache Spark. - Experience with Databricks and MLOps tools like MLflow. - Experience with cloud, preferably in Azure. - Ability to exhibit strong communication and customer-facing skills. - Ability to thrive both independently and in cross-functional teams. - Ability to problem solve and stay current with emerging ML trends. Nice If You Have - Experience with full-stack development or deploying end-to-end ML applications. - Experience with chatbot development or conversational AI. - Experience fine-tuning large models. - Experience with deploying ML solutions using MLOps pipelines. - Knowledge of Agile workflows and tools like JIRA. Benefits - Join a fast-growing, award-winning team that values professional development, collaboration, and innovation. - At JRSS, our employees are our greatest asset — and your work will directly support high-impact federal and enterprise missions. Company Description JRSS is an IT consulting service provider for Government and Fortune 500 clients. As a certified WOSB, SDB, and HUBZone small business, we specialize in Federal Civilian Data, Cloud, and AI/ML enterprise-level solution architecture, design, implementation, and professional staffing. Recognized on the Inc. 5000 list of fastest-growing private companies, we're proud to foster a collaborative culture where innovation and client impact come first.
• Collaborate with cross-functional teams to deliver high-quality AI-driven applications • Design scalable systems and justify technical decisions • Implement event-driven architecture and asynchronous workflows • Mentor team members on AI engineering best practices • Drive technical leadership initiatives within the team
At Axians, we value talent — not labels. We believe in a culture of inclusion, where everyone has a place. All applications are considered based on merit, with no discrimination of any kind. This is your opportunity to join an international group, working on a project that needs you to help tackle the challenges of digital transformation.
Role Description We are looking for a #TechTalent to take on the role of AI Engineer for a project in the logistics sector . - Collaborate with cross-functional teams to identify business needs and potential areas where AI solutions can add value; - Design and develop proof-of-concepts (PoCs) using machine learning and deep learning techniques to demonstrate the feasibility and potential impact of AI-driven solutions; - Evaluate and validate the performance of PoCs, considering factors such as accuracy, scalability, and computational efficiency; - Work closely with stakeholders to understand their feedback and requirements, iterating on PoCs to enhance their value and address specific business challenges; - Analyze the outcomes of PoCs and identify the most promising concepts with significant business value; - Translate successful PoCs into minimum viable products (MVPs), working collaboratively with software engineers and data scientists to productize and scale the solutions; - Optimize and fine-tune AI models and algorithms to meet performance requirements and align with business objectives; - Conduct thorough testing and validation of MVPs, ensuring their reliability, stability, and usability in real-world scenarios; - Collaborate with product teams to integrate AI capabilities into existing systems or develop new AI-driven applications; - Stay informed about industry trends, advancements, and best practices in AI engineering and leverage this knowledge to drive innovation in PoC and MVP development; - Document the development process, methodologies, and results, providing clear and concise reports and presentations to stakeholders; - Provide technical guidance and support to junior AI engineers, fostering knowledge sharing and continuous learning within the team. Qualifications - Bachelor's or master's degree in computer science, data science, artificial intelligence, Mathematics or a related field; - Proven experience working as an AI Engineer, machine learning engineer, or similar role; - Solid understanding of LLMs, machine learning and deep learning techniques, algorithms, and frameworks (e.g., TensorFlow, PyTorch, Keras, LangChain); - Proficiency in programming languages such as Python and Java, and experience with relevant libraries and tools for data manipulation, analysis, and visualization (e.g., NumPy, pandas, Matplotlib); - Experience with big data processing and distributed computing frameworks (e.g., Hadoop, Spark) is a plus; - Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services; - Strong problem-solving skills and ability to translate business requirements into technical solutions; - Excellent communication and teamwork abilities, with the capacity to collaborate effectively with cross-functional teams; - Strong attention to detail; - A self-driven and proactive attitude, with a passion for learning and staying updated on emerging technologies and industry trends; - Provide technical guidance and support to junior AI engineers, fostering knowledge sharing and continuous learning within the team. Benefits - Opportunity to lead major projects; - Recognition as a professional and as a person; - Work Life Balance and premium benefits; - Possibility to become a shareholder in the company; - Stability and job security; - Fair compensation.
Role Description The AI Engineer is responsible for delivering value through the delivery of AI solutions to core business functions. This role focuses on applying industry AI techniques, tools, and platforms to develop scalable, production-ready systems that solve real business problems. - Own defined initiatives end-to-end, ensuring measurable impact. - Work closely with product, wider engineering teams, and business stakeholders. - Balance technical excellence with strong ways of working. - Contribute to a culture of accountability, trust, and continuous improvement. This role requires strong applied AI engineering skills across architecture, software engineering, and MLOps, combined with the ability to communicate effectively and drive business-aligned outcomes. Qualifications - Strong applied AI engineering skills. - Experience in architecture, software engineering, and MLOps. - Effective communication skills. - Ability to drive business-aligned outcomes. Company Description A global leader in applied safety science, UL Solutions (NYSE: ULS) transforms safety, security and sustainability challenges into opportunities for customers in more than 110 countries. - Delivers testing, inspection and certification services. - Offers software products and advisory offerings that support product innovation and business growth. - The UL Mark serves as a recognized symbol of trust in customers’ products. - Helps customers innovate, launch new products and services, navigate global markets and complex supply chains. - Supports sustainable and responsible growth into the future.
The Competition aims to challenge students and improve their skills as future international lawyers.
• Design, build, and deploy production ML and LLM-based systems (RAG, agentic workflows, fine-tuning, embeddings) for enterprise clients • Own technical delivery end-to-end: from architecture and prototyping to deployment, monitoring, and iteration • Work directly with client engineering and product teams to translate business needs into scoped, shippable technical solutions • Mentor and support other ML engineers on the team — code reviews, technical guidance, and knowledge sharing • Help shape internal best practices, tooling, and technical standards as the team grows • Represent TensorOps technically in client conversations, workshops, and (optionally) at industry conferences
• Design, develop, and deploy AI-powered applications, agents, and automation solutions that improve business processes and customer experiences. • Build and maintain production-grade backend services, APIs, and integrations using Python and modern cloud technologies. • Develop workflow automations that support Sales, Revenue Operations, Customer Support, and other business functions. • Create and optimize data pipelines and integrations across enterprise platforms including Salesforce, Microsoft 365, Freshdesk, and other business systems. • Design and implement retrieval-augmented generation (RAG) architectures, LLM orchestration frameworks, and evaluation methodologies. • Lead the development of AI-powered simulation experiences, including conversational and voice-enabled learning solutions. • Identify opportunities to embed AI capabilities into existing BARBRI products and rapidly deliver high-impact features. • Partner closely with product, engineering, and business stakeholders to understand needs, define solutions, and deliver measurable outcomes. • Enable non-technical teams by providing guidance, training, and best practices for building and maintaining AI agents and automations.
• Continuous LLM Evaluation: Design and operate a systematic, ongoing process to evaluate new and emerging LLMs across accuracy, relevancy, speed, and cost — continuously benchmarking them against the specific tasks in our orchestration pipeline proactively optimizing outcomes. • Eval Framework Development: Build and maintain rigorous evaluation frameworks (Evals) to measure LLM output accuracy, relevance, faithfulness, and speed with a specific focus on reducing hallucinations in medical record summarization and legal document analysis. • Proactive Model Transition Planning: Monitor the LLM landscape across providers to identify deprecation timelines and suitable replacement models — and own the full execution of those transitions, including integrating new models into the production pipeline and maintaining necessary changes to account for model behavior. • AI Pipeline Optimization: Directly implement optimizations to LLM-based orchestration pipelines for document understanding, medical record summarization, case chronology generation, and drafting support — owning code changes, deployments, and production validation from start to finish. • Cross-Functional Collaboration: Partner with product and GTM stakeholders to communicate model evaluation findings — then lead the technical implementation yourself rather than delegating execution to a separate engineering team. • End-to-End Implementation Ownership: Take full responsibility for shipping model changes into production — writing the integration code, managing deployments, running validation tests, and ensuring a clean rollout. • Operational Monitoring: Implement monitoring and observability for model performance in production, benchmarking outputs and cost, detecting drift with ongoing and continuous reporting to management. • Documentation: Maintain thorough documentation of evaluation methodologies, model comparison results, transition decisions, and runbooks for the systems you own.
Leveraging AQ - the powerful compound effects of AI + Quantum technology
• Bring novel ideas and the content of scientific papers into high-performing and robust scientific code. • Lead the ideation, benchmarking, and execution of complex datasets and ML models, ensuring seamless integration into our large-scale simulation frameworks. • Drive software through the entire product lifecycle—from foundational research and implementation to launch and long-term support—ensuring technical excellence at every stage.
AI Driven Personalized & Conversational Email / SMS Marketing for leading ecom brands.
• Produce a high volume of content across formats - short-form video, long-form YouTube, static and video ads, LinkedIn posts, written pieces, landing page and email creative - using AI tooling to multiply your output well beyond what a traditional content team can match. • Build the factory: repeatable systems and workflows (AI tooling, templates, freelancers, repurposing pipelines) so content scales without linearly scaling headcount. • Run and optimize paid ads directly off the content you create (Meta, LinkedIn, Reddit, and beyond) - launch, test, read the data, iterate, kill losers, scale winners. • Turn our raw material - product stories, customer wins, founder POV, data insights - into a constant stream of native, on-brand content. • Move fast and ship daily, treating volume plus iteration speed as the advantage.
• Architect, build, and maintain AI‑first web and mobile applications using modern frameworks and engineering best practices. • Lead the development of AI‑powered features using Python, LangGraph, and modern LLM tooling. • Design and implement agentic workflow applications, including orchestration, tool use, stateful flows, and human‑in‑the‑loop patterns. • Develop end‑to‑end solutions across the front end, back end, APIs, and cloud infrastructure. • Write clean, scalable, and maintainable code in TypeScript (Node), JavaScript (React), and Python using established design patterns. • Optimize applications for speed, scalability, reliability, and long‑term maintainability. • Work closely with cross‑functional teams to define, design, and ship new features with strong ownership of outcomes. • Provide architectural guidance, code reviews, and mentorship to engineering teams. • Partner with clients to lead demos, support rollout discussions, and ensure successful adoption of AI‑powered solutions.
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Cloud, Google Cloud Platform, Python, Azure, JavaScript, AWS
