Hardware Machine Learning PhD Research Internship

ittihad medical centre; Chicago (IL); On-site; USD 202,500 - 247,500; Full time

Benefits offered by this job

Discretionary bonus

Paid leave

Health insurance

Job summary

ittihad medical centre in Chicago is offering a PhD internship focused on machine learning applied to custom hardware. Interns will work directly with engineers on real projects, presenting their findings and contributing to innovative solutions in low-latency ML inference.

Ideal candidates should be currently enrolled in a PhD program in fields such as Electrical Engineering or Computer Science and possess a solid understanding of hardware constraints and ML fundamentals. The role offers a competitive base salary of $225,000 along with benefits and a discretionary bonus.

Qualifications

• Solid understanding of hardware design trade-offs relevant to ML models.
• Experience with ML frameworks like PyTorch and TensorFlow.
• Ability to work collaboratively with technical and non-technical teams.

Responsibilities

• Architect and develop an ML project in a real-world trading environment.
• Work hands-on with hardware engineers to deploy ML solutions.
• Present your research findings to the team and contribute insights.

Skills

Understanding of hardware constraints

Proficiency in Python

Strong communication skills

Education

Currently enrolled in a PhD program in a relevant field

Tools

VHDL/SystemVerilog

ML-to-hardware frameworks

Job description

We are deploying machine learning directly onto custom hardware – and we want you to help drive it forward. This PhD internship is an opportunity to work on research that has direct impact on IMC's work tackling open problems at the frontier of low-latency ML inference and hardware acceleration.

You'll work alongside IMC engineers in one of the most demanding low-latency computing environments in the world. You'll own a focused research project from start to finish, present your findings to the team, and leave behind a prototype or benchmark that we can build on.

Your Core Responsibilities

• Architect and develop an ML focused research project based on a real-world trading environment
• Work hands-on with hardware engineers to implement, verify, and deploy ML inference solutions
• 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
• Present your project to the team, deepening our collective understanding of an area of ML acceleration
• Gain hardware design fundamentals from skilled RTL developers and learn how they apply to our industry
• Build skills to evaluate research not only from an academic perspective, but through real-world performance constraints, engineering costs, and industry impact

Your Skills and Experience

• Currently enrolled in a PhD program in Electrical Engineering, Computer Science, Physics, or a related field
• 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 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

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. Benefits – US | IMC Trading.

Base Salary: $225,000