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Causal Inference Machine Learning Postdoctoral Jobs in New Jersey

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · On-site

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Implement model optimization techniques for mobile (on-device) and cloud inference. * Apply fraud ...

Compunnel

ML Engineer

Jersey City, NJ · On-site

Build and deploy APIs and services to serve machine learning models * Optimize model inference for speed, scalability, and efficiency * Develop automated pipelines for model training, testing, and ...

Compunnel

ML / Ops Engineering

Jersey City, NJ · On-site

Integrate machine learning workflows with data platforms such as Spark, Kafka, Airflow, and feature stores * Optimize compute and GPU usage for large-scale model training and inference Required ...

Cisco

Principal Machine Learning Engineer

Iselin, NJ

$291K - $369K/yr

... and inference efficiency to minimize cost and latency while preserving accuracy. * MLOps ... Learning - Fluency in automated retraining, drift detection, incremental updates, and production ...

Walmart

(USA) Principal, Data Scientist

Clifton, NJ · On-site

$132K - $264K/yr

As a Principal Data Scientist at Walmart, you will lead the development and deployment of advanced analytical models Leveraging sophisticated techniques such as Double Machine Learning and Causal ...

Walmart

(USA) Principal, Data Scientist

Hackensack, NJ · On-site

$132K - $264K/yr

As a Principal Data Scientist at Walmart, you will lead the development and deployment of advanced analytical models Leveraging sophisticated techniques such as Double Machine Learning and Causal ...

Walmart

(USA) Principal, Data Scientist

Bayonne, NJ · On-site

$132K - $264K/yr

As a Principal Data Scientist at Walmart, you will lead the development and deployment of advanced analytical models Leveraging sophisticated techniques such as Double Machine Learning and Causal ...

Walmart

(USA) Principal, Data Scientist

East Orange, NJ · On-site

$132K - $264K/yr

As a Principal Data Scientist at Walmart, you will lead the development and deployment of advanced analytical models Leveraging sophisticated techniques such as Double Machine Learning and Causal ...

Walmart

(USA) Principal, Data Scientist

Paterson, NJ · On-site

$132K - $264K/yr

As a Principal Data Scientist at Walmart, you will lead the development and deployment of advanced analytical models Leveraging sophisticated techniques such as Double Machine Learning and Causal ...

Walmart

(USA) Principal, Data Scientist

Hoboken, NJ · On-site

$143K - $286K/yr

As a Principal Data Scientist at Walmart, you will lead the development and deployment of advanced analytical models Leveraging sophisticated techniques such as Double Machine Learning and Causal ...

Walmart

(USA) Principal, Data Scientist

Passaic, NJ · On-site

$132K - $264K/yr

As a Principal Data Scientist at Walmart, you will lead the development and deployment of advanced analytical models Leveraging sophisticated techniques such as Double Machine Learning and Causal ...

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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, and why are they important?

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.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in New Jersey? For Causal Inference Machine Learning Postdoctoral jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in New Jersey look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in New Jersey are:
What cities in New Jersey are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities in New Jersey with the most Causal Inference Machine Learning Postdoctoral job openings:
Causal Inference Machine Learning Postdoctoral jobs near you
AI / Machine Learning Engineer

AI / Machine Learning Engineer

1Kosmos

Iselin, NJ • On-site

Full-time

PTO

Re-posted 5 days ago

Job description

Are you ready to shape the future of authentication? Join 1Kosmos and help lead the next wave in identity assurance and passwordless innovation.
1Kosmos is driving the future of identity security, empowering organizations to eliminate passwords and establish trust at every step of the identity lifecycle. As a vibrant team of innovators, we develop advanced authentication solutions trusted by some of the world's leading brands. Join us as we create a passwordless world and set new standards for digital identity assurance.
We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer vision and AI solutions. You will work on projects involving image capture, data extraction, and fraud detection, delivering high-performance models that can run on both mobile devices and cloud environments.
This role blends R&D with production engineering-you'll take ownership of the full ML lifecycle, from dataset creation and model training to deployment and performance optimization.
Key Responsibilities
  • Design and implement AI models for image classification, object detection, OCR, and feature extraction.
  • Develop real-time image quality assessment and capture guidance algorithms.
  • Create and maintain data pipelines for collecting, cleaning, augmenting, and labeling datasets.
  • Implement model optimization techniques for mobile (on-device) and cloud inference.
  • Apply fraud detection methods to identify tampering, forgeries, or replay attacks in visual data.
  • Integrate ML models into production-grade APIs and mobile SDKs.
  • Monitor, evaluate, and continuously improve model accuracy and performance.
  • Collaborate with product and engineering teams to align AI capabilities with business goals.

Requirements
  • Bachelor's or Master's degree in Computer Science, AI/ML, or related field (or equivalent experience).
  • 3+ years of experience building and deploying ML models in production.
  • Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar).
  • Experience with computer vision libraries (e.g., OpenCV) and OCR technologies.
  • Strong understanding of deep learning architectures for image and text recognition.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and API development.
  • Strong problem-solving skills and ability to work in fast-paced environments.
  • Based in the NJ / NY area; Hybrid working model.
Preferred Qualifications
  • Experience with model quantization and optimization for mobile deployment.
  • Knowledge of synthetic data generation and data augmentation techniques.
  • Background in security, liveness detection, or anomaly detection.
  • Exposure to compliance and data privacy regulations (GDPR, CCPA).
  • Contributions to open-source ML projects or published research.

Benefits
  • Cutting-Edge Tech Stack: Build with decentralized identity protocols, FedRamp High, FIDO2-certified cryptography, and NIST-compliant biometric systems.
  • Accelerated Growth: Receive annual stipends for certifications and attend key conferences like Identiverse or EIC.
  • Ownership & Impact: We move fast and will enable you to make a big impact with large customers in US & Canada.
  • Flexibility First: Unlimited PTO, and 2 days WFH

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