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Causal Inference Machine Learning Postdoctoral Jobs in Connecticut

AMC Health

Senior Software Engineer Applied AI

Hartford, CT ยท On-site

$123K - $162K/yr

... 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 ...

New

Commonfund

AI/ML Development Analyst

Norwalk, CT ยท On-site

$100K - $150K/yr

Design, develop, and deploy machine learning and AI-driven solutions for business and financial ... Develop and maintain data pipelines, model training workflows, and inference services . * Analyze ...

Catalyst Labs

ML Engineer

Greenwich, CT ยท On-site

Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data ... inference, and monitoring in production environments. โ€ข Participate in continuous improvement of ...

Catalyst Labs

ML Engineer

Stamford, CT ยท On-site

Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data ... inference, and monitoring in production environments. โ€ข Participate in continuous improvement of ...

Pwc

AI Engineer

Stamford, CT ยท On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... using quantization, inference acceleration, and model-routing techniques - Designing agent ...

Pwc

AI Engineer

Hartford, CT

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... using quantization, inference acceleration, and model-routing techniques - Designing agent ...

HomeServe

AI Solutions Architect

Norwalk, CT ยท On-site

$126 - $168/hr

Experience designing architectures for AI-powered applications, generative AI, machine learning, or ... inference, and prompt management. * Experience integrating conversational AI platforms with ...

HomeServe

AI Solutions Architect

Norwalk, CT ยท On-site

$63.25 - $83.25/hr

Experience designing architectures for AI-powered applications, generative AI, machine learning, or ... inference, and prompt management. * Experience integrating conversational AI platforms with ...

HomeServe

AI Solutions Architect

Norwalk, CT ยท On-site

$125K - $167K/yr

Experience designing architectures for AI-powered applications, generative AI, machine learning, or ... inference, and prompt management. * Experience integrating conversational AI platforms with ...

HomeServe USA

AI Solutions Architect

Norwalk, CT ยท On-site

$63.25 - $83.50/hr

Experience designing architectures for AI-powered applications, generative AI, machine learning, or ... inference, and prompt management. * Experience integrating conversational AI platforms with ...

Varsity Tutors

LSAT Logical Reasoning Tutor

Stamford, CT ยท Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Varsity Tutors

LSAT Logical Reasoning Tutor

New Haven, CT ยท Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Varsity Tutors

LSAT Logical Reasoning Tutor

Norwalk, CT ยท Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Cisco

Applied AI Scientist

Stamford, CT ยท On-site

Develop and enhance distributed training and inference workflows, leveraging data-driven approaches ... Large-scale graph representation learning and Graph Neural Networks (GNNs) (e.g., GCN/GAT/GraphSAGE ...

Varsity Tutors

LSAT Logical Reasoning Tutor

Bridgeport, CT ยท Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Varsity Tutors

LSAT Logical Reasoning Tutor

Hartford, CT ยท Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

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All JobsCausal Inference Machine Learning Postdoctoral JobsCausal Inference Machine Learning Postdoctoral Jobs in Connecticut

Causal Inference Machine Learning Postdoctoral information

What is a causal inference machine learning postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a causal inference machine learning postdoctoral researcher?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by causal inference machine learning postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

Is it difficult to get a causal inference machine learning postdoctoral position?

Securing a causal inference machine learning postdoctoral position can be competitive due to specialized skills required, such as expertise in statistical methods, programming (e.g., Python or R), and a strong research background. Candidates with relevant publications, strong recommendations, and experience in machine learning frameworks often have better chances, but the availability of such positions varies by institution and funding.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Connecticut?

For Causal Inference Machine Learning Postdoctoral jobs in Connecticut, the most frequently searched job titles are:

What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Connecticut look for?

The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Connecticut are:

What cities in Connecticut are hiring for Causal Inference Machine Learning Postdoctoral jobs?

Cities in Connecticut with the most Causal Inference Machine Learning Postdoctoral job openings:

Causal Inference Machine Learning Postdoctoral jobs near you
Infographic showing various Causal Inference Machine Learning Postdoctoral job openings in Connecticut as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution.

Senior Software Engineer Applied AI

AMC Health

Hartford, CT โ€ข On-site

$123K - $162K/yr

Full-time

This job post hasย expired today.ย Applications are no longer accepted.

Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems)
AMC Health ๏ฟฝ Remote (US) ๏ฟฝ 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