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Temporary Machine Learning Quant Jobs in Romeoville, IL

IMC Inc

Hardware Machine Learning Engineer

Chicago, IL

$200K - $225K/yr

Hardware Machine Learning Engineer Chicago, United States; New York, United States We are deploying ... Architect and co-design ML models with traders, quant researchers, and software engineers, treating ...

IMC

Hardware Machine Learning Engineer

Chicago, IL

$200K - $225K/yr

Architect and co-design ML models with traders, quant researchers, and software engineers, treating ... Understanding of machine learning fundamentals - neural network architectures, inference ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

Architect and co-design ML models with traders, quant researchers, and software engineers, treating ... Understanding of machine learning fundamentals - neural network architectures, inference ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$127K - $167K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Architect and co-design ML models with traders, quant researchers, and software engineers, treating ...

PayPal

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

PayPal, Inc.

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

3Red Partners

Quant

Chicago, IL · On-site

$150K - $250K/yr

The Quant will have the opportunity to work in one of our offices focusing on expanding and ... Experience with Python, C++, and machine learning tools * Ability to understanding the optimization ...

3Red Partners

Quant

Chicago, IL

$150K - $250K/yr

The Quant will have the opportunity to work in one of our offices focusing on expanding and ... Experience with Python, C++, and machine learning tools * Ability to understanding the optimization ...

Akuna Capital

Quantitative Researcher

Chicago, IL · On-site

$145K/yr

Akuna's Trading and Research teams are seeking Quant Researchers to join a multidisciplinary group ... Design and optimize machine learning workflows to support scalable, efficient, and reproducible ...

Akuna Capital

Quantitative Researcher

Chicago, IL · On-site

$145K/yr

Akuna's Trading and Research teams are seeking Quant Researchers to join a multidisciplinary group ... Design and optimize machine learning workflows to support scalable, efficient, and reproducible ...

IMC

Quantitative Researcher - Futures

Chicago, IL · On-site

... machine learning techniques to derive forecasts that will be combined with IMC's best-in-class ... Several years (5+ Years) of quantitative research experience, preferably in systematic trading ...

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All JobsTemporary Machine Learning Quant JobsTemporary Machine Learning Quant Jobs in Romeoville, IL

Temporary Machine Learning Quant information

See Romeoville, IL salary details

$53.5K

$121.5K

$200.4K

How much do temporary machine learning quant jobs pay per year?

As of Jun 21, 2026, the average yearly pay for temporary machine learning quant in Romeoville, IL is $121,502.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,000.00 and $155,500.00 per year, depending on experience, location, and employer.

Do JP Morgan hire quants?

JP Morgan hires quantitative analysts and machine learning quants for roles in risk management, trading, and investment strategies. These positions typically require strong programming skills, knowledge of financial models, and advanced degrees in quantitative fields. The firm values expertise in tools like Python, R, and machine learning frameworks.

What is the difference between Temporary Machine Learning Quant vs Quantitative Analyst?

AspectTemporary Machine Learning QuantQuantitative Analyst
CredentialsDegree in Computer Science, Data Science, or related fields; programming skills in Python, R, or C++Degree in Finance, Economics, or Mathematics; strong analytical skills
Work EnvironmentTech-driven, research-focused, often in financial firms or hedge fundsFinancial institutions, investment banks, asset management firms
Industry UsageCommon in quantitative trading, algorithm development, and data-driven finance rolesUsed for risk management, trading strategies, and financial modeling

The Temporary Machine Learning Quant and Quantitative Analyst roles share overlapping skills in data analysis and finance but differ mainly in focus. The Machine Learning Quant emphasizes programming, algorithm development, and machine learning techniques, often in tech-heavy environments. In contrast, the Quantitative Analyst leans more toward financial modeling, market analysis, and risk assessment. Both roles are vital in finance but cater to different technical and strategic needs.

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

To excel as a Temporary Machine Learning Quant, you need strong quantitative analysis skills, proficiency in machine learning algorithms, and an advanced degree in a quantitative field such as mathematics, statistics, computer science, or engineering. Hands-on experience with programming languages like Python or R, familiarity with data analysis libraries (e.g., NumPy, pandas), and exposure to financial systems or platforms are typically required. Exceptional problem-solving abilities, adaptability, and effective communication help you stand out in this fast-paced environment. These competencies are crucial for developing and deploying data-driven models that inform trading strategies and deliver measurable business impact.

What are the typical responsibilities and challenges faced by a Temporary Machine Learning Quant in a financial firm?

As a Temporary Machine Learning Quant, you will often be tasked with quickly analyzing large financial datasets to develop and validate predictive models for trading strategies or risk assessment. Adapting to new team environments and rapidly understanding proprietary data systems can be challenging, especially given the short-term nature of the role. You'll collaborate closely with traders, data engineers, and other quants to implement solutions, and are usually expected to deliver actionable insights within tight deadlines. The fast-paced setting provides exposure to cutting-edge technologies and can be a stepping stone to more permanent quant or data science positions.

What does a Temporary Machine Learning Quant do?

A Temporary Machine Learning Quant is a professional who applies machine learning techniques to financial data and quantitative models, typically on a short-term or project-based contract. Their work may involve researching, developing, and implementing algorithms to analyze market trends, forecast prices, or optimize trading strategies. These roles are often found in investment banks, hedge funds, or fintech companies, and require strong programming, statistical, and financial skills. The 'temporary' aspect indicates the position is not permanent and usually fills a specific project or resource gap.

Is 40 too old to become a quant?

Age is generally not a barrier to becoming a quantitative analyst or machine learning quant, as skills in programming, mathematics, and finance are more important. Many professionals transition into quant roles later in their careers by acquiring relevant certifications, such as CFA or advanced degrees, and developing expertise in data analysis and modeling tools.

Are quant jobs replaceable by AI?

Quant jobs, including those for machine learning quants, involve complex analysis, model development, and decision-making that currently require human expertise. While AI tools can automate certain tasks like data processing and model testing, the need for critical thinking, domain knowledge, and oversight keeps these roles relevant. Continuous learning and proficiency with programming languages like Python or R are essential in this field.

Which 5 jobs will survive AI?

For a Temporary Machine Learning Quant, roles that require complex judgment, creativity, and domain expertise are more likely to survive AI automation, such as strategic analysis, client communication, and regulatory compliance. Jobs involving advanced problem-solving, programming, and understanding of financial markets will also remain in demand, especially when combined with skills in data analysis and machine learning tools. Continuous learning and adapting to new technologies are essential for long-term job security in this field.
What cities near Romeoville, IL are hiring for Temporary Machine Learning Quant jobs? Cities near Romeoville, IL with the most Temporary Machine Learning Quant job openings:
Temporary Machine Learning Quant jobs near you

Hardware Machine Learning Engineer

IMC Inc

Chicago, IL

$200K - $225K/yr

Other

PTO

Posted 6 days ago

Job description

Hardware Machine Learning Engineer

Chicago, United States; New York, United States

We are deploying machine learning directly onto custom hardware – and we want you to help drive it from the ground up. This is an initiative where you'll have the rare opportunity to architect solutions from scratch, influence technical research direction, and see your work drive real impact in one of the most demanding computing environments in the world.

We build the hardware, the software, and the infrastructure, so when you hit a bottleneck, you can fix it - there's no vendor to wait on and no abstraction layer you're not allowed to touch. If you've ever wanted to push the boundaries of what's computationally possible, this role is for you. We're looking for researchers and experienced engineers from any background. Trading experience is a bonus, not a prerequisite.

Your Core Responsibilities
  • Architect and co-design ML models with traders, quant researchers, and software engineers, treating hardware constraints (latency budgets, resource limits, numerical precision) as first-class design inputs
  • Shape our custom hardware roadmap by translating ML model requirements into concrete architectural decisions
  • Work hands-on with hardware engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production
  • Track and evaluate emerging research in neural architecture search, machine learning systems and quantization methods, and determine what translates to measurable improvements in our systems
Your Skills and Experience
  • Solid understanding of hardware constraints and design trade-offs (e.g., pipelining, resource utilization, fixed-point arithmetic) that shape how ML models can be efficiently mapped onto FPGAs or custom ASICs
  • Experience with hardware fundamentals, whether through VHDL /SystemVerilog development, HLS tools, or ML-to-hardware frameworks like hls4ml, FINN, or Vitis AI
  • Understanding of machine learning fundamentals – neural network architectures, inference optimization, quantization techniques, ML frameworks such as PyTorch/TensorFlow
  • Proficiency in Python, C++, or similar languages for tooling, testing, and simulation
  • Strong communication skills and ability to work collaboratively across disciplines with both technical and non-technical teams
Nice to Have
  • Exposure to ML compiler infrastructure such as MLIR, TVM, XLA, or similar tools for lowering and optimizing models for hardware targets
  • Background in latency-sensitive or resource-constrained systems including high-frequency trading, particle physics data acquisition, real-time signal processing, or similar domains
  • Familiarity with functional verification methodologies (for example SystemVerilog, UVM, Cocotb)
  • Advanced degree (MS or PhD ) in EE, CS, Physics, or related field, or equivalent depth through industry or research experience

The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information.

Salary Range

$200,000 - $225,000 USD

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we've been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

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