Backed by a world-class team - including ICPC champions, a Fields Medalist and an ACM Turing Award winner - we're building the future where all code is provably correct. About the role Join our team ...
Backed by a world-class team - including ICPC champions, a Fields Medalist and an ACM Turing Award winner - we're building the future where all code is provably correct. About the role Join our team ...
Turing information
See Chicago, IL salary details
$9.13 - $14.06
16% of jobs
$15.57 is the 25th percentile. Wages below this are outliers.
$14.06 - $19
29% of jobs
The median wage is $20.23 / hr.
$19 - $23.93
19% of jobs
$28.31 is the 75th percentile. Wages above this are outliers.
$23.93 - $28.87
12% of jobs
$28.87 - $33.80
8% of jobs
$33.80 - $38.74
5% of jobs
$38.74 - $43.67
4% of jobs
$43.67 - $48.61
2% of jobs
$48.61 - $53.54
2% of jobs
$53.54 - $58.48
1% of jobs
$58.48 - $63.41
1% of jobs
$9
$27
$63
How much do turing jobs pay per hour?
As of Aug 23, 2026, the average hourly pay for turing in Chicago, IL is $27.04, according to ZipRecruiter salary data. Most workers in this role earn between $15.54 and $31.58 per hour, depending on experience, location, and employer.
What is a Turing job?
A Turing job is a remote software engineering position offered through Turing.com, a platform that connects developers with top companies worldwide. Turing uses AI-driven matching to pair engineers with roles that fit their skills, experience, and preferences. These jobs are typically long-term, full-time positions with competitive salaries and opportunities to work with leading tech firms without needing to relocate.
What type of projects and clients can Turing engineers expect to work with?
Turing engineers are connected with clients ranging from fast-growing startups to large enterprises across a wide variety of industries, such as fintech, e-commerce, health tech, and more. The nature of projects can vary—some may involve building new applications from scratch, while others might focus on optimizing or extending existing systems. Engineers typically collaborate with remote teams in agile environments, requiring adaptability and clear virtual communication. This diversity gives you a chance to build a broad portfolio, gain exposure to cutting-edge technologies, and enhance your skills through challenging assignments.
What are the key skills and qualifications needed to thrive in the Turing position, and why are they important?
To succeed as a Turing engineer (a software engineer employed by Turing), you typically need a strong background in computer science, software development, and proficiency in relevant programming languages such as Python, JavaScript, or Java. Familiarity with version control systems like Git, cloud platforms, and experience with remote collaboration tools are common technical requirements; certifications in software development can be a plus. Excellent communication, self-motivation, and problem-solving skills are crucial for collaborating with distributed teams and adapting to diverse project needs. These abilities enable you to deliver high-quality code, collaborate effectively in a remote environment, and thrive in demanding, fast-paced tech projects.
What are the most commonly searched types of Turing jobs in Chicago, IL?
The most popular types of Turing jobs in Chicago, IL are:
Other
Posted 10 days ago
Job description
Logical Intelligence, we're revolutionizing software development with AI-powered formal verification. We've developed groundbreaking agents that provide mathematical guarantees of code correctness, ensuring that software behaves exactly as intended while proactively identifying bugs and security vulnerabilities. Our novel foundation model enables scalable, precise reasoning for formally verifiable code across Rust, Golang, and smart contract VMs. We’ve won a well-known formal verification benchmark called PutnamBench, which consists of 672 hard math problems from the William Lowell Putnam Exam, the oldest collegiate mathematics competition in North America. Backed by a world-class team – including ICPC champions, a Fields Medalist and an ACM Turing Award winner – we're building the future where all code is provably correct.
About the role
Join our team as an AI Research Engineer and help us push the boundaries of what's possible in logical reasoning! We’re looking for a motivated individual to build, maintain, and improve innovative approaches including (but not limited to!) energy-based modeling (EBM). You'll be at the forefront of designing and refining algorithms that go beyond the capabilities of traditional Large Language Models (LLMs), tackling complex reasoning challenges. You'll work closely with a talented team of AI experts, EBM specialists, formal verification engineers, and software developers to create groundbreaking solutions.
What you'll do
- Research new reasoning algorithms and models
- Pre-train and fine-tune the State-of-the-Art LLMs
- Combine Reasoning algorithm and LLMs
- Build effective and efficient ML pipelines
- Collaborate with other teams to understand their pain points and priorities to define milestones of the corresponding roadmaps
- Derive practical solutions and integrate them with the results of other teams to provide the best overall resolution.
Qualifications
- M.Sc. or Ph.D. (preferable) focusing on one or more of the following areas: Computer Science, Artificial Intelligence, Mathematics, or a closely related field
- 5+ years of subject matter expertise and research in one or more of the following areas: Machine Learning, Deep Learning, Reasoning, Energy-based Modeling (preferable)
- Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning including Deep Learning frameworks like PyTorch /TensorFlow/JAX
- Strong communication and teamwork skills
- Experience with explicit and implicit reasoning
- Demonstrated research publications in any of the major conferences (CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI, ACL, etc.
Bonus Points
- Provable record of Energy-based usage for different problems
- Hands-on with algorithms used to train Energy-based models
- Multi-node and multi-GPU training
- Mathematical Reasoning – discrete math and logic
- Formal Verification - lean