Senior Python Engineer

Wizard

ABOUT WIZARD AI At Wizard AI, we’re building the top-performing AI Shopping Agent that delivers the best products from across the web with unmatched accuracy, quality, and trust. Our ML models power the core of our platform, and we’re looking for a Senior Machine Learning Engineer to own how they run in production reliably, efficiently, and at scale. THE ROLE As a Senior ML Engineer on our Inference Platform, you’ll own the end-to-end lifecycle of production ML serving systems from model packaging and deployment to monitoring, optimization, and scaling. This is not a traditional MLOps role focused solely on pipelines and tooling. You’ll be responsible for the inference infrastructure powering a live conversational shopping agent, operating multiple specialized serving engines under real-world production load. You’ll own critical decisions around serving architecture, performance, reliability, and scalability, working closely with ML Engineers, Data teams, Product, and DevOps to ensure models move seamlessly from experimentation into high-performance production systems. WHAT YOU'LL DO * Own and evolve our multi-engine inference platform, supporting a variety of model types and serving requirements. * Build and improve production ML pipelines — taking models from experimentation to reliable, high-throughput serving. * Define and implement model versioning, rollout, rollback, and lifecycle management strategies that ensure reproducibility and operational reliability. * Define and enforce serving-layer SLAs, including latency, availability, GPU utilization, Time-to-First-Token (TTFT), and Inter-Token Latency (ITL). * Build observability, monitoring, alerting, and operational tooling for production inference systems. * Apply software engineering best practices, including testing, CI/CD integration, and reproducibility across ML workflows. * Optimize inference performance through efficient resource utilization, hardware-aware serving strategies, and cost-conscious infrastructure design. * Ensure ML serving systems are secure, scalable, and operationally resilient. * Partner with ML, Data, Product, and DevOps teams to turn ideas into production systems, driving the technical decisions on serving and scale. WHAT WE'RE LOOKING FOR * Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience. * 5–8+ years of experience in Software Engineering, ML Engineering, Platform Engineering, or Infrastructure Engineering, with direct ownership of production ML serving systems. * Hands-on experience running an LLM serving engine (vLLM, TGI, TensorRT-LLM, or SGLang) in production under real load — not just managed or hosted endpoints. * Strong Python skills and software engineering fundamentals, combined with deep systems and infrastructure knowledge. * Experience with cloud platforms such as AWS, GCP, or Azure, and familiarity with ML lifecycle tooling, experimentation platforms, and model registries. * Strong grasp of inference performance — continuous batching, KV-cache and GPU-memory behavior, quantization, and CPU-versus-GPU bottlenecks — with the instinct to profile before tuning. * Experience serving heterogeneous workloads, including LLMs, embedding models, and extraction models, each with distinct latency, throughput, and scaling requirements. * Demonstrated ability to balance latency, throughput, reliability, and infrastructure cost while operating production-scale ML systems. * Experience in high-growth startup environments and comfort operating in fast-moving, evolving technical landscapes. WHAT SUCCESS LOOKS LIKE RELIABLE, SCALABLE INFERENCE SYSTEMS Production serving infrastructure operates with clear SLAs, strong observability, and minimal downtime. Latency, availability, throughput, and GPU utilization are actively measured and optimized as platform demands grow. END-TO-END OWNERSHIP You own the complete serving lifecycle — from deployment and release management through monitoring, optimization, and scaling — enabling ML engineers to ship quickly while maintaining reliability and reproducibility. TECHNICAL LEADERSHIP AND IMPACT You shape the future of Wizard's inference platform, driving key architectural decisions that improve performance, reduce infrastructure costs, and support the next generation of AI-powered shopping experiences.

Wizard

ABOUT WIZARD Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust. THE ROLE We’re looking for an Applied Scientist to own how we measure, understand, and improve the accuracy of our AI agent. This role sits at the intersection of applied ML, evaluation science, and product. You’ll define what “good” looks like for our agent, build the systems to measure it, and lead the science work to improve it, including fine-tuning the LLM judges that power our evaluation pipeline. You’ll partner with ML Engineering and AI Engineering. What you will do is bring scientific rigor to the most important question at Wizard: is our agent getting better, and how do we know? This is a foundational hire on our science team. Evaluation is the starting point, and the role is scoped to grow into broader applied science work as the surface area of the agent expands (recommendations, personalization, ranking, multimodal, conversational understanding). WHAT YOU’LL DO * Define and evolve accuracy metrics across the full shopping experience (retrieval, ranking, recommendations, outcomes) * Design and run experiments to measure improvements and regressions * Build and maintain evaluation datasets, benchmarks, and scoring frameworks * Improve the LLM judges that power our evaluation pipeline: prompting, calibration, and fine-tuning where it matters * Translate ambiguous product questions into clear, measurable hypotheses and analysis * Partner with ML Engineers to validate model changes and guide iteration * Identify failure modes and edge cases, and drive improvements through data * Make agent performance visible, trusted, and actionable across product and engineering FIRST 3 MONTHS * Go deep on the agent, the current eval pipeline, and the metrics we use today * Audit existing accuracy metrics and benchmarks; identify gaps, blind spots, and signals that aren’t trustworthy * Build relationships with ML, AI Engineering, and Product * Ship one quick win: a missing benchmark, an improved metric, or a fix to a misleading signal * Establish a baseline view of agent performance the team can rally around MONTHS 3 TO 6 * Own the evaluation framework: datasets, metrics, scoring, reporting, both offline and online * Drive measurable improvements to LLM judge quality (calibration, fine-tuning where appropriate) * Run experiments that influence at least one significant model or product change * Stand up automated evaluation the team trusts before and after every launch * Build dashboards and reporting that make agent performance legible to leadership BEYOND 6 MONTHS * Lead applied science work on the next frontier as the agent grows: multi-turn evaluation, multimodal, personalization, ranking quality, conversational understanding * Influence team-level strategy on what we measure, what we improve, and why * Mentor and help grow the science function as it expands WHAT SUCCESS LOOKS LIKE * Clear, trusted accuracy metrics are consistently used across product and engineering * A robust automated evaluation framework for both offline and live experiments * Model and product changes are consistently measured before and after launch * Demonstrable improvements in LLM judge quality and eval coverage * Science leadership that informs what we build, not just whether it works CAREER GROWTH * Depth track: become the org’s authority on AI evaluation: eval strategy, judge models, agent benchmarking * Breadth track: expand into other applied science problems (recommendations, personalization, ranking, multimodal, conversational understanding) as those areas come online * Leadership track: Senior / Staff Applied Scientist, with technical leadership across the science function * As the agent gets more capable, the science problems get richer IDEAL BACKGROUND * 5+ years in Applied ML, AI Research, or Applied Science (PhD or equivalent depth strongly preferred) * Hands-on experience evaluating modern AI/ML systems: LLMs, agents, ranking, or recommendations * Direct experience with LLM-based systems: judge models, RAG, prompt engineering, fine-tuning, RLHF, or similar * Strong experimentation foundations: A/B testing, causal inference, statistical rigor * Proven ability to operate in ambiguity: defining problems, not just solving pre-defined ones * Clear, structured communication that influences across ML, engineering, and product COMPENSATION & BENEFITS The expected base salary range for this role is $225,000 - $280,000 USD, and will vary based on skills, experience, role level, and geographic location. Final compensation will be determined by considering these factors alongside overall role scope and responsibilities. In addition to base salary, Wizard offers: * Equity in the form of stock options * Medical, dental, and vision coverage * 401(k) plan * Flexible PTO and company holidays * Fully remote work within the United States * Periodic company offsites and team gatherings Wizard is committed to fair, transparent, and competitive compensation practices.

Man Group

About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance 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 $228.7 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com At Man Group, we respect your privacy and we are committed to protecting and safeguarding your Personal Data. We have developed policies and processes which are designed to provide for the security and integrity of your Personal Data. We are committed to Processing your Personal Data fairly and lawfully, and being open and transparent about such Processing. For further information on how we process your data, please see the privacy notice for applicants here * As at 31 March 2026   The Role  We’re seeking Senior Python Engineers to join various teams across our technology organisation, working on diverse challenges spanning systematic trading, quantitative research, a petabyte-scale data platform, and AI solutions.  The role offers the opportunity to collaborate with and learn alongside highly skilled engineers whilst developing core technical and financial services knowledge. You will work with cutting-edge technologies and systems that power critical areas of Man Group’s business.    Role Responsibilities  * Design and maintain scalable backend systems and APIs that support quantitative research and trading infrastructure * Develop distributed compute applications, optmise performance, and implement monitoring and observability tooling to ensure system reliability * Build high-performance data pipelines for processing large-scale financial datasets using timeseries, SQL, and NoSQL databases * Partner with engineers, researchers, and platform teams to translate complex requirements into technical solutions that integrate with Man Group’s technology estate * Participate in production support rotations and contribute to architecture decisions, code reviews, and engineering best practices across the team * You should have the enthusiasm for leveraging AI development tools to accelerate delivery and driving their adoption across the team.   Our Technology  You’ll work in a modern, Linux-based infrastructure where Python is the primary development language, utilising the full scientific stack including pandas, numpy, scipy, and scikit-learn. A key component of our data infrastructure is ArcticDB (https://arcticdb.io/), our internally developed DataFrame database that you’ll use extensively. We maintain a dynamic technology landscape, continuously evaluating and adopting new tools and libraries that enhance our capabilities. man.com/technology    Key Competencies  Essential  * Minimum 5 years’ professional software development experience in any object-oriented language. Python experience is preferred, though we are open to candidates proficient in other object-oriented languages who are willing to learn Python. * Strong academic record with coursework focused on mathematical and computing content e.g. Computer Science, Mathematics, Engineering or Science * Experience developing mission-critical production systems, with knowledge of best practices for testing, monitoring, and deployment Proficient on Linux platforms and strong understanding of Git * Strong knowledge of one or more relevant database technologies e.g. MS SQL, Postgres, or MongoDB * Demonstrated experience working with large data sets, both structured and unstructured * Ability to work independently and gather requirements from stakeholders * Embracing agentic engineering — willingness and ability to work effectively with AI -assisted development tools as part of daily workflow   Advantageous * Deep understanding of the Python scientific stack (pandas, numpy, scipy, scikit-learn)  * Familiarity with distributed systems and orchestration  * Knowledge of modern data engineering practices including data pipeline & ETL tools, distributed storage & processing and data warehousing  * Contributions to open-source projects  * Experience working with Large Language Models (LLMs)  * Experience mentoring junior team members and managing projects    Why Man Group?  * Work on challenging problems at the cutting edge of technology and finance   * Collaborate with world-class engineers, researchers, and investment professionals  * Receive on-the-job training to develop and succeed at the firm   * Entrepreneurial, innovation-driven culture  * Small, agile teams with high autonomy  * Opportunity to make a real impact on investment strategies managing billions in assets    Benefits   * Modern office located in the OfficeX campus with easy access to transport and amenities. * Hybrid working model * Competitive compensation package * 25 days holiday allowance * Premium Health insurance * Employee Assistance program * Referral Bonus * Additional days off for long service and volunteering * Multisport card * Opportunities for professional development including internal tech talks * Conference attendance, and engagement with the open-source community Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity. You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering. Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance. Equal Employment Opportunity Policy Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws. Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.