Software Engineer Boston; Massachusetts

Man Group is a global alternative investment management firm focused on pursuing out performance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent.

Headquartered in London, we manage $213.9 billion
* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is of the FTSE 250 Index. Further information can be found at

* As at 30 September 2025

As a Software Engineer in the Front-office Engineering organization at Man Numeric, you will work closely with Quantitative Researchers and Portfolio Managers. Your challenges will be varied and may include onboarding new datasets, implementing new trading signals, developing portfolio optimization tools, building data visualization frameworks, enhancing our research platform, and performance tuning existing code using efficient numerical algorithms and cluster-computing solutions.

Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack:
Num Py, Sci Py, Pandas, stats models, and scikit-learn to name a few of the libraries we use extensively. We implement the systems that require the highest data throughput in Java. For storage, we rely heavily on Mongo

DB and MS SQL.

We use Control‑M and Airflow for workflow management, Kafka for data pipelines, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, ELK for log shipping and monitoring, Docker for containerisation, Open Stack for our private cloud, Ansible for architecture automation, and Slack for internal communication. Our technology list is never static: we constantly evaluate new tools and libraries.

Man Numeric has a small company, no‑attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader technology community.

• We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See @manquanttech
• We host and sponsor Boston meetups and London’s PyData and Machine Learning Meetups

We’re fortunate enough to have a fantastic open‑plan office overlooking the Boston harbour, and continually strive to make our environment a great place in which to work. We believe that agile working allows us to deliver the best business outcomes for our clients and investors as well as having a positive impact on work‑life balance and the wellbeing of our staff.

We are simultaneously committed to “levelling the playing field” and believe that agile working promotes inclusivity across teams, regions and business units. In general, Technology roles are expected to be in the office for 3 days a week. However, the specifics can vary based on the role, team, and individual circumstances, and are ultimately subject to the manager’s discretion.

We offer competitive compensation, a generous holiday allowance, various health and other flexible benefits. We are also committed to continuous learning and development via coaching, mentoring, regular conference attendance and sponsoring academic and professional qualifications.

We strive to hire only the brightest, best and most highly skilled, passionate technologists.

• 2‑3 years of professional experience in software engineering, preferably with a focus on quantitative applications
• Proficiency in Python and experience with scientific libraries including Pandas, Num Py, Sci Py, stats models and scikit‑learn
• Experience working on production systems, with an understanding of best practices…