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Applied Ai Engineer Jobs in Riverside, NJ (NOW HIRING)

AMC Health

Senior Software Engineer Applied AI

Trenton, NJ · On-site

$122K - $161K/yr

Senior Software Engineer: Applied AI (Voice Agents & ML Systems) AMC Health Remote (US) Full-time The pitch We build and operate production AI voice agents that hold real phone conversations in a ...

New

Sia

Applied AI Lead

Philadelphia, PA · On-site

We're looking for an Applied AI Lead to join Sia's ETI practice and help clients move AI ... Work directly with client engineering, data, and IT/OT teams to understand system constraints and ...

Sia

Applied AI Lead

Philadelphia, PA · On-site

We're looking for an Applied AI Lead to join Sia's ETI practice and help clients move AI ... Work directly with client engineering, data, and IT/OT teams to understand system constraints and ...

Sia

Applied AI Lead

Philadelphia, PA · On-site

We're looking for an Applied AI Lead to join Sia's ETI practice and help clients move AI ... Work directly with client engineering, data, and IT/OT teams to understand system constraints and ...

Sia

Applied AI Lead

Philadelphia, PA · On-site

We're looking for an Applied AI Lead to join Sia's ETI practice and help clients move AI ... Work directly with client engineering, data, and IT/OT teams to understand system constraints and ...

Sia

Applied AI Lead

Philadelphia, PA · On-site

We're looking for an Applied AI Lead to join Sia's ETI practice and help clients move AI ... Work directly with client engineering, data, and IT/OT teams to understand system constraints and ...

Cisco

Applied AI Scientist

Philadelphia, PA

Collaborate with engineering, product, and data science teams to understand requirements, incorporate stakeholder feedback, and deliver AI/ML solutions that address business and technical needs.

Fingerpaint Group

Product Manager

Philadelphia, PA · Hybrid

Role Overview The Product Manager, Applied AI, is a strategic conduit between the business and the agency's AI product engineers for one or more products. You partner with business sponsors to deeply ...

New

Fingerpaint Group

Product Manager

Philadelphia, PA · Hybrid

Role Overview The Product Manager, Applied AI, is a strategic conduit between the business and the agency's AI product engineers for one or more products. You partner with business sponsors to deeply ...

Fingerpaint Group

Product Manager

Philadelphia, PA · On-site

Role Overview The Product Manager, Applied AI, is a strategic conduit between the business and the agency's AI product engineers for one or more products. You partner with business sponsors to deeply ...

Fingerpaint Group

Product Manager

Philadelphia, PA · Hybrid

Role Overview The Product Manager, Applied AI, is a strategic conduit between the business and the agency's AI product engineers for one or more products. You partner with business sponsors to deeply ...

New

Burro

Senior Robotics AI Engineer

Philadelphia, PA · On-site

$160K - $180K/yr

We are seeking a Senior Robotics AI Enginee r with strong applied machine learning and robotics ... The ideal candidate will have a strong grasp of robotics and software engineering fundamentals ...

Cigna

Technical Product Manager - Applied AI

Philadelphia, PA · On-site +1

$168K - $194K/yr

Technical Product Manager - Applied AI We are seeking an experienced technical product manager to ... This role will work closely with Finance process owners, Engineering, Data, and Architecture ...

New

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Showing results 21-40

All JobsApplied Ai Engineer JobsApplied Ai Engineer Jobs in Riverside, NJ

Applied Ai Engineer information

What are the key skills and qualifications needed to thrive as an applied AI engineer?

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What are some common challenges applied AI engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.

What is the difference between Applied Ai Engineer vs Data Scientist?

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

How much does an applied AI engineer make?

An applied AI engineer's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to earn higher salaries.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

What cities near Riverside, NJ are hiring for Applied Ai Engineer jobs?

Cities near Riverside, NJ with the most Applied Ai Engineer job openings:

Applied Ai Engineer jobs near you

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Trenton, NJ • On-site

$150 - $260/hr

Other

Re-posted 7 days ago

Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems) The pitch

We build and operate production AI voice agents that hold real phone conversations in a regulated healthcare setting, plus the machine learning and LLM pipelines around them. This is one seat that spans four disciplines that rarely come together: real‑time systems, LLM engineering, traditional machine learning, and serious cloud infrastructure, all in production, all with real consequences. If you are the kind of engineer who gets restless doing one thing, this role is the opposite problem.

What you’ll work across
  • Streaming, low‑latency speech‑to‑speech systems built on modern LLMs
  • Telephony and real‑time media (call control, live audio streaming)
  • Audio handling and the quirks of real human conversation (interruptions, timing, noise)
  • Concurrency on a latency‑sensitive path, where p99 matters and a stall is something a caller hears
  • Wrapping nondeterministic models in deterministic control so they behave reliably in production
  • Multi‑model pipelines, prompt design, and cost/latency budgeting
  • Evaluation harnesses, including LLM‑as‑judge and automated agent‑tests‑agent approaches
  • Agentic tooling that gives AI systems safe, structured access to infrastructure
Traditional (non‑LLM) machine learning
  • End‑to‑end ML pipelines: feature engineering, model training, and scheduled inference
  • Imbalanced, messy real‑world data; calibration and explainability for non‑technical consumers
  • Turning research notebooks into reproducible, auditable production pipelines
Cloud and infrastructure
  • Infrastructure as code across multiple environments (we run on AWS)
  • Managed compute, data, streaming, and orchestration services
  • Security engineering in a regulated setting: encryption, least‑privilege access, strict data‑handling discipline
  • Observability and telemetry‑driven debugging, tracing a production issue from a metric anomaly to root cause
Plus

Occasional full‑stack work on internal tools, and an engineering workflow that leans heavily on AI coding assistants, with human accountability for every change.

What you’ll actually do
  • Ship and debug code on a live, real‑time voice pipeline where latency and correctness are user‑facing
  • Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
  • Build and operate LLM evaluation and batch‑analysis pipelines
  • Own traditional ML workflows from data to scheduled production inference
  • Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor
Must‑haves
  • 7+ years building and operating production backend systems, with strong general‑purpose programming skills (we work primarily in Python)
  • Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
  • Hands‑on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
  • Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
  • Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data
Nice‑to‑haves
  • Real‑time media or telephony experience
  • Front‑end / full‑stack ability
  • ML pipeline experience, vector search, or embeddings
  • Fluency with AI coding assistants (our workflows assume them, with human accountability for every change)
How we work

Smallest correct change wins. Every behavior change is validated against the live system. Evidence over opinion in debugging. Code review is rigorous. Safety and privacy gate everything.

This role is open only to US citizens and lawful permanent residents (Green Card holders). We cannot consider candidates who require visa sponsorship now or in the future, and we are unable to make exceptions of any kind.

How to apply
  • Your LinkedIn profile URL
  • A phone number where we can reach you

A resume is welcome but optional; the two items above are required.

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