Polar Operations LLC (dba IMC Markets) has multiple openings for Python Software Engineer (REQ#4461661101) in Chicago, IL and Brooklyn, NY.

Your Core Responsibilities

• Implement software features and components for IMC's trading systems (25%).
• Design software solutions independently and make architectural decisions (10%).
• Debug and fix software issues in trading systems (5%).
• Identify complex multi-component issues, perform root cause analysis, and implement preventative solutions (5%).
• Ensure code quality and system reliability through comprehensive automated testing (10%).
• Contribute to the automated testing framework, own critical trading system components, and ensure reliability, performance, and scalability across regions (5%).
• Participate in code reviews (10%).
• Monitor system performance and trading operations (5%).
• Collaborate with traders and other teams to understand requirements and deliver solutions (10%).
• Participate in planning, estimate complexity of tasks, and help balance technical debt with feature development (5%).
• Mentor and guide junior developers and interns, helping them understand IMC's systems and development practices (10%).

Partial telecommuting permitted. Multiple positions available. Requisition #: 4461661101

Your Skills and Experience

This position requires a Bachelor’s degree, or foreign equivalent, in Computer science, Computer Engineering, or a similarly quantitative and technical field and one (1) year of experience in the job offered or a related occupation.

Must have at least one (1) year of experience in each of the following skill(s):

• Applying analytical and engineering techniques to solve complex problems programmatically;
• Programming with Python;
• Developing and implementing algorithms and data structures;
• Software development lifecycle and best practices;
• Designing and developing software applications in a collaborative, cross-functional environment;
• Experience with DevOps, databases, big data, or frontend frameworks;
• Experience with Docker, Kubernetes, and Linux environments;
• Experience working with financial data;
• Foundational knowledge of quantitative trading concepts and equity/index options;
• Exposure to web/API frameworks such as FastAPI and React;
• Experience with automated testing and CI/CD pipelines;
• Experience collaborating with trading desks and developing software for use in a quantitative trading environment;
• Experience with the following tools: Team City, JIRA ticket management, Gerrit code review tool, GitLab, uv, Gitlab CI, py-spy, memray, and Python Packaging; and
• Experience with the following libraries: Pandas, Polars, NumPy, Tensorflow, Scikit, scikit-learn, cvxpy, and Pytest.

#LI-DNI

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

Lantern is looking for a Director of AI Engineering to lead the strategy, development, and delivery of AI and machine learning capabilities across the organization. This is a senior leadership role responsible for building and scaling a high-performing AI engineering team, setting the technical vision for ML/LLM systems, and ensuring that AI initiatives are tightly aligned with Lantern’s product strategy, care workflows, and business objectives. You will report to the VP of Engineering and work closely with executive leadership to shape how AI transforms care delivery and operations at Lantern.

In this role, you will own the end-to-end AI engineering function—from research and prototyping through production deployment and continuous improvement. You will be expected to move fast, driving rapid proof-of-concept development and delivering production-grade AI solutions on aggressive timelines. You will establish the technical roadmap, define engineering standards, build team culture, and drive execution across multiple concurrent AI initiatives. Your work will directly impact how Lantern leverages intelligent systems to improve patient outcomes, operational efficiency, and scalable growth.

Location: Hybrid - at least 3 days/wk in one of our offices:  Dallas, TX / Chicago/Evanston / New York / Washington, DC

Responsibilities:

• Define and execute the AI engineering strategy and technical roadmap, ensuring alignment with Lantern’s product, clinical, and business priorities.
• Build, lead, and scale a high-performing AI engineering team, including hiring, mentoring, performance management, and creating a culture of technical excellence and innovation.
• Drive rapid AI proof-of-concept development, moving from problem identification to working prototypes on aggressive timelines, and shepherding successful POCs into production-grade systems.
• Own the end-to-end lifecycle of ML/LLM systems—from research and experimentation through production deployment, monitoring, and continuous improvement.
• Establish and maintain best-in-class MLOps practices: experiment tracking, reproducibility, CI/CD for models, automated testing, drift detection, observability, and scalable infrastructure on Azure.
• Partner with product, clinical operations, marketing, data, and engineering leadership to identify high-impact AI opportunities and translate them into well-scoped, executable initiatives.
• Lead architecture decisions for ML/LLM systems, ensuring scalability, reliability, security, and compliance with healthcare regulations.
• Establish clear KPIs and success metrics for the AI engineering function, including model performance, delivery velocity, team health, and business impact.
• Champion responsible AI practices across the organization, including fairness, transparency, explainability, and regulatory compliance in healthcare contexts.
• Represent the AI engineering function to executive leadership, providing regular updates on progress, risks, and strategic recommendations.
• Build external visibility for Lantern’s AI capabilities through thought leadership, community engagement, and talent brand building.

Experience & Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience; Master’s preferred.
• 10+ years of experience in software engineering or machine learning, with at least 4 years in a leadership role managing ML/AI teams.
• Proven track record of building and shipping production ML/LLM systems at scale, including end-to-end ownership from research through deployment.
• Deep technical expertise in ML frameworks (PyTorch, TensorFlow, scikit-learn), LLM technologies (prompt engineering, RAG, embeddings, fine-tuning, agents), and modern MLOps practices.
• Strong experience with cloud-native ML infrastructure on Azure, including Azure ML, Databricks, and Azure DevOps pipelines.
• Demonstrated ability to rapidly prototype AI solutions and drive them to production on aggressive timelines.
• Experience with big data ecosystems (Spark, Databricks, Delta Lake) and streaming technologies.
• Excellent leadership skills: hiring and developing high-performing teams, managing cross-functional relationships, and influencing at the executive level.
• Strong strategic thinking with the ability to balance long-term vision with near-term execution and business impact.
• Experience operating in regulated environments, ideally healthcare, with an understanding of compliance, data governance, and responsible AI principles.
• Outstanding communication skills with the ability to translate complex technical concepts for non-technical stakeholders and executive audiences.

Strong Candidates will have:

• Experience applying AI/ML capabilities in healthcare, health tech, or other regulated industries.
• Background working with clinical data, claims data, or healthcare operational workflows.
• Experience building and scaling AI teams from the ground up, including defining team structure, processes, and culture.
• Track record of delivering AI-powered products that drove measurable business outcomes.
• Experience with LLM agents, agentic workflows, tool-use orchestration, or multi-step reasoning systems.

Benefits

• Medical Insurance
• Dental Insurance
• Vision Insurance
• Short & Long Term Disability
• Life Insurance
• 401k with company match
• Paid Time Off
• Paid Parental Leave

Job Title: Research Professional – Oeindrila Dube - AI and Machine Learning for Social Impact  (Full-Time, Benefits Eligible)

Location: Chicago, IL 

Salary Ranges: $55,000–62,000 annual salary, additional $2,000 professional development fund. The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.

Terms: Seeking a Research Professional for a period of at least one but ideally two years 

Expected Start Date: July 1, 2026 

Department: Becker Friedman Institute  

Benefits Eligible: Yes. The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.

About the program

The Becker Friedman Institute for Economics (BFI) is seeking to hire a full-time Research Professional to work with Professor Oeindrila Dube. Applicants must have completed a Bachelors degree by June 2026 and available to begin work in summer 2026. The Research Professional’s responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical analyses, running simulations, and preparing manuscripts and presentations. 

The program is intended to serve as a bridge between college and graduate school for students interested in empirical economics. Applicants must have strong quantitative and programming skills. Candidates with research experience are strongly preferred, especially those with experience in Stata, R, Python or Matlab. The ideal candidate would work for BFI for one or two years before applying to graduate school in Economics or another quantitative social science. BFI offers competitive salary and employee benefits. 

Job Summary 

Can cutting-edge AI make policing more equitable?  Can we infer what is in a police officer’s mind from observing their behavior? These are the kinds of question driving our research program, and we're looking for someone to help answer them. 

The Becker Friedman Institute for Economics (BFI) is seeking a full-time Research Professional to work with Oeindrila Dube, Philip K. Pearson Professor at the University of Chicago's Harris School of Public Policy. This is a hands-on research role at the frontier of computer science and economics, with real stakes: the projects you'll work on aim to change how police interact with the public.  

We are applying NLP and machine learning to terabytes of body-worn camera footage to build tools that improve policing outcomes. We will evaluate the effectiveness of these tools using experimental methods. This work builds on "A Cognitive View of Policing" (QJE 2025). You will be working at real scale, using data that matters.  

The ideal candidate has strong training in computer science and economics or a related social science field. While you don’t need to have majored in economics, you should be excited to learn how economists think about leveraging NLP/AI tools and generate causal evidence. 

Why this, instead of a software job? 

If you're a CS student weighing this against a position in industry: the work here is harder in different ways, more collaborative, and the output is knowledge that gets published and used to inform real policy decisions. Pre-doctoral research positions like this one are a well-established pathway into PhD programs in economics, computer science, public policy, and related fields — and a growing number of CS researchers have found that combining their technical skills with training in causal inference opens up research questions that neither field can tackle alone. 

Unit-preferred Competencies

• Strong programming skills in Python, including experience with at least some machine learning libraries (e.g., scikit-learn, PyTorch, Hugging Face) 
• Has experience working with large structured/unstructured datasets in a research or internship setting
• Ability to work independently and manage multiple projects simultaneously 
• Excellent organizational skills 
• Attention to detail 
• Strong academic writing/communication skills

Minimum Qualifications:

Education

• Bachelor's degree in CS, economics, statistics, math, or a related quantitative discipline

Experience

• At least one year of relevant research experience (coursework and school projects count)

Technical Knowledge/Skills

• Knowledge of R and/or Python preferred 
• Knowledge of STATA preferred 

Preferred Qualifications:

• Has experience in NLP, speech/ASR, or computer vision. 
• Has experience with R and Stata are a plus (as Stata is used in the field experiment work) 
• Has had exposure to causal inference or program evaluation — or is eager to develop these skills quickly.  

Application Documents

• Resume/CV (required)
• Cover Letter (required)
• Writing Sample (required)
• Transcripts (unofficial is acceptable) (required)
• Two Professional References (required)

About the Department  

The Becker Friedman Institute for Economics aims to foster frontier research and apply those findings to achieve global impact. BFI brings together researchers from the Booth School of Business, the Kenneth C. Griffin Department of Economics, the Harris School of Public Policy, the Law School, and the entire University of Chicago Economics Community to leverage robust data, apply cutting-edge analytical tools, and uncover novel insights on the world’s most difficult economic problems. BFI then bridges the divide between academic researchers and relevant policy makers by translating and packaging rigorous research into accessible formats and proactively sharing those findings with decision-makers and thought leaders in business, government and nonprofit institutions. In this way, BFI has the potential to play a significant role in meeting the most difficult challenges facing the global community. 

The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University’s Notice of Nondiscrimination.

Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

All offers of employment are contingent upon a background check that includes a review of conviction history.  A conviction does not automatically preclude University employment.  Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

The University of Chicago’s Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: http://securityreport.uchicago.edu. Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.