Interested in this AI/ML Engineer role at Mission Lane?
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About This Role
Mission Lane is combining the power of data, technology, and exceptional service to pave a clear way forward for millions of people on the path to financial success. By attracting top talent and leveraging cutting\-edge technology, we're enabling people to unlock real financial progress. Sound like a mission you can get behind?
We're looking for a leader with an uncompromising eye for detail, a deep background in complex direct mail cycles, and the technical fluency to build scalable marketing operations programs to join our team as the Senior Manager, Marketing Operations.
The Impact You'll Make
You'll drive forward our mission of empowering people to unlock financial progress by bridging the critical gap between creative strategy and technical execution for our direct mail marketing channel.
At its core, our mission depends on our ability to deliver the best fit credit offers to individuals who can benefit from them the most; your work ensures that these opportunities are delivered with absolute precision. Your primary objective is to evolve our Direct Mail engine into a flawless, scalable system that supports this essential connection.
As Senior Manager, Marketing Operations, you will:
- Serve as the final quality gatekeeper for all marketing campaigns, ensuring every offer, term, and disclosure is perfectly mapped in our highly regulated financial environment.
- Own and execute the Direct Mail technology roadmap, partnering with Engineering and Data teams to design scalable workflows.
- Identify opportunities to automate data processing and campaign building, reducing manual steps and accelerating our time\-to\-launch.
- Lead the production lifecycle, managing print vendor relationships, postal logistics (USPS), and inventory to optimize pricing.
- Directly manage and develop the marketing operations team, fostering a culture of uncompromising attention to detail and continuous growth.
- Improve and maintain robust documentation and processes for responding to audits with transparency and integrity.
Minimum Qualifications:
- 7\+ years in Marketing Operations or Program Management, with specific experience managing complex, recurring direct mail cycles.
- Proven experience in a regulated industry where precision and compliance are essential.
- Technical proficiency in managing roadmaps and understanding complex data logic, such as segmentation and offer mapping.
- Experience managing direct reports and successfully influencing cross\-functional technical teams like Data and Engineering.
- Hands\-on experience managing print vendors, mail shops, and postal logistics.
- Ability to travel as needed.
Preferred Qualifications:
- Direct marketing experience within the credit card or financial services industry.
- Experience moving a team from manual workflows to automated systems.
Compensation:
Annual full\-time starting base salary range: $134,000 \- $158,000
This role is eligible for additional compensation in the forms of participation in our annual incentive and equity programs.
Pay is based on factors such as work experience, education, certification(s), training, skills, and competencies related to the role. Mission Lane also offers a comprehensive benefits plan, which includes paid time off, 401(k) match, a monthly wellness stipend, health/ dental/ vision insurance options, disability coverage, paid parental leave, flexible spending account (for childcare and healthcare), life insurance, and a remote\-friendly work environment.
\#LI\-DNI
About Mission Lane:
Founded in December 2018, Mission Lane is a purpose\-driven fintech company based in the U.S., with headquarters in Richmond, Virginia.
It all started with a realization: nearly fifty percent of the adult population in the U.S. doesn't have access to a clear line of credit. Most traditional credit card companies either overlook or overcharge this group because they have less\-than\-perfect credit scores or no scores at all. We decided this just wouldn't do.
In partnership with our sponsor banks, we offer credit cards under the Mission Lane brand name, with better, clearer terms, and a more refined customer experience than the alternatives available to people working hard to improve their credit. To date, over four million consumers have chosen Mission Lane, earning high customer ratings on Credit Karma for its market segment and industry leading Net Promoter scores.
Mission Lane has cumulatively raised over $600 million of equity from leading investors, including Invus Opportunities, QED Investors, LL Funds, funds affiliated with Oaktree Capital Management, and other leading investors.
Our commitment to a workplace built on respect and dignity is guided by our core value of Unity. We believe that everyone plays a vital role in our shared purpose, and we actively cultivate an environment where all individuals have the opportunity to do their best work. By fostering a culture of empathy and collaboration, we create a strong sense of belonging and support for every team member.
Mission Lane is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, or any other protected status.
Mission Lane provides reasonable accommodations to applicants who need them for medical or religious reasons, as required by law. Applicants can initiate an accommodation request by contacting peopleexperience@missionlane.com.
Mission Lane is not sponsoring new applicant employment authorization and please, no third\-party recruiters.
Application Integrity:
Our cardholders trust us with their financial well\-being, and this trust starts with the integrity of the people on our team. We're looking for team members who share our dedication to transparency and truth. Please verify that the information in your application is accurate and complete.
*Providing any information to Mission Lane that is not completely truthful at any point during the application or hiring process may result in removal from the hiring process, disqualification from future opportunities, withdrawal of an offer or other sanctions for candidates and, in addition for employees, disciplinary action, up to and including termination of employment.*
Salary Context
This $134K-$158K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Mission Lane, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($146K) sits 13% below the category median. Disclosed range: $134K to $158K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Mission Lane AI Hiring
Mission Lane has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $158K - $158K.
Location Context
AI roles in New York pay a median of $200,000 across 1,670 tracked positions. That's 9% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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