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Assistant Machine Learning Quant Jobs in Plainfield, IN

Guidehouse

Model Validation Lead

Indianapolis, IN · On-site

... machine learning, and AI models deployed in federal environments. You will lead model validation ... Master's degree or PhD in a quantitative or technical discipline What We Offer: Guidehouse offers a ...

Guidehouse

Model Validation Lead

Indianapolis, IN · On-site

... machine learning, and AI models deployed in federal environments. You will lead model validation ... Master's degree or PhD in a quantitative or technical discipline What We Offer: Guidehouse offers a ...

Aerotek

Machine Operator

Indianapolis, IN

$15 - $17.75/hr

... * Assist with machine setup, changeovers, cleaning, and preventive maintenance activities to ... The environment offers tremendous learning and growth opportunities as the team refines processes ...

Keystone Cooperative

ML Engineer

Indianapolis, IN · On-site

... * Assist in developing machine learning models and algorithms to solve complex business problems and improve operational efficiency. * Create and maintain detailed documentation of data analysis ...

Keystone

ML Engineer

Indianapolis, IN · On-site

... * Assist in developing machine learning models and algorithms to solve complex business problems and improve operational efficiency. * Create and maintain detailed documentation of data analysis ...

TSMG

AI/ML Data Contributor

Indianapolis, IN · On-site

In this role, you will participate in tasks that help improve machine learning models, including ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Indianapolis, IN

In this role, you will participate in tasks that help improve machine learning models, including ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Indianapolis, IN

In this role, you will participate in tasks that help improve machine learning models, including ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Indianapolis, IN · Remote

In this role, you will participate in tasks that help improve machine learning models, including ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Indianapolis, IN

In this role, you will participate in tasks that help improve machine learning models, including ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Indianapolis, IN · On-site

In this role, you will participate in tasks that help improve machine learning models, including ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Indianapolis, IN

In this role, you will participate in tasks that help improve machine learning models, including ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Indianapolis, IN · Remote

In this role, you will participate in tasks that help improve machine learning models, including ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

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All JobsMachine Learning Quant JobsAssistant Machine Learning Quant JobsAssistant Machine Learning Quant Jobs in Plainfield, IN

Assistant Machine Learning Quant information

See Plainfield, IN salary details

$13

$17

$22

How much do assistant machine learning quant jobs pay per hour?

As of Jul 19, 2026, the average hourly pay for assistant machine learning quant in Plainfield, IN is $17.71, according to ZipRecruiter salary data. Most workers in this role earn between $16.06 and $18.85 per hour, depending on experience, location, and employer.

What are Assistant Machine Learning Quants?

Assistant Machine Learning Quants are entry-level professionals in quantitative finance who support senior quants by applying machine learning techniques to analyze financial data, build predictive models, and develop trading strategies. Their responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They work closely with quantitative researchers and traders to improve algorithmic trading systems and risk management processes. This role typically requires strong programming skills, a solid understanding of machine learning concepts, and familiarity with financial markets.

How does an Assistant Machine Learning Quant typically collaborate with senior quants and data scientists on projects?

As an Assistant Machine Learning Quant, you will often work closely with senior quantitative researchers and data scientists by supporting model development, data preprocessing, and feature engineering tasks. You may contribute to brainstorming sessions, implement prototypes, and assist in backtesting trading strategies or risk models. This collaborative environment provides valuable mentorship opportunities and exposure to best practices in quantitative analysis and machine learning within the finance industry. Effective communication and a willingness to learn from senior team members are key to success in this role.

What are the key skills and qualifications needed to thrive as an Assistant Machine Learning Quant, and why are they important?

To thrive as an Assistant Machine Learning Quant, you need strong quantitative skills, a background in statistics or mathematics, and typically a degree in a STEM field. Familiarity with programming languages such as Python or R, experience with machine learning frameworks, and knowledge of financial modeling tools are essential. Strong problem-solving abilities, attention to detail, and effective communication are standout soft skills in this role. These competencies enable accurate model development, efficient data analysis, and clear collaboration with team members in high-stakes financial environments.
What job categories do people searching Assistant Machine Learning Quant jobs in Plainfield, IN look for? The top searched job categories for Assistant Machine Learning Quant jobs in Plainfield, IN are:
Assistant Machine Learning Quant jobs near you
Infographic showing various Assistant Machine Learning Quant job openings in Plainfield, IN as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $36,837 per year, or $17.7 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Indianapolis, IN • Remote

$117K - $154K/yr

Full-time

Posted 4 days ago

Job description

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 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

Real-time voice AI

  • 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

LLM engineering

  • 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.

Work authorization (no exceptions)

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

Please submit both of the following:

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

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

Apply