Sr. Machine Learning Engineer - Finance | JobSetuu

Description

Job Overview

• Source: The Muse

Job Description

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and curiosity to your job and there's no telling what you could accomplish. Do you love thinking analytically? Just as our customers find value in Apple products, the Finance group finds value for both Apple and its shareholders.

As a machine learning engineer in Finance, you'll play an integral role in building the data foundations, services, and platforms used for delivering insights and automating decisions for Apple's Finance organization.

Description

This role will be the technical lead for product cost, supporting our Operations Finance organization. You will work as part of a multi-discipline engineering pod with data and software engineers, product managers and program managers. Your ability to learn business processes and instill strong engineering practices into team machine learning processes will be critical. A key part of your role will be to operationalize AI solutions, bridging the gap between prototype and production to rapidly and reliably deliver value to the Finance organization.

Responsibilities:

Technical lead overseeing solution design and engineers

Partner with teammates and share expertise across teams

Explain technical concepts to non-technical audiences

Collaborate effectively with cross-functional teams

Operationalize AI solutions, bridging the gap between prototype and production

Instill strong engineering practices into team machine learning processes

Rapidly and reliably deliver value to the Finance organization

Preferred Qualifications

Previous experience working in a corporate finance, accounting, or supply chain organization

Understanding of or ability to learn financial statements, P&L impact, high level accounting principles, SOX and tax compliance and month-end close process

Minimum Qualifications

Graduate degree (computer science, data science, math, quantitative finance, or similar discipline)

Seven or more years of experience building data driven solutions

Experience leading engineers and collaborating cross-functionally, translating technical concepts for diverse audiences and converting ideas into solutions with strong process and data understanding

Experience building data models and scalable pipelines using SQL and big data technologies, with expertise in data ops best practices

Experience developing in Python while following DRY principles, modularity, and testing standards, with version control, code review. Experience with front end (.js experience)

Experience applying ML algorithms for regression, classification, and anomaly detection; build generative AI and agentic solutions; implement MLOps/LLMOps including CI/CD, drift monitoring, and cloud platforms (AWS, GCP, Azure)

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Expert Career Tips for Sr. Machine Learning Engineer - Finance Roles

To succeed in a competitive market as a Sr. Machine Learning Engineer - Finance, you need more than just technical skills. Here are some expert strategies to elevate your profile:

• Build a Strong Portfolio: For technical roles, a clean GitHub or a personal project site is essential. For non-technical roles, a case study portfolio demonstrating problem-solving and impact is equally valuable. Show, don't just tell, what you have achieved in your previous positions.
• Master the Narrative: When interviewing, use the STAR method (Situation, Task, Action, Result) to structure your answers. Quantify your results wherever possible—mentioning "increased efficiency by 20%" is much more impactful than saying "improved efficiency."
• Continuous Learning: The industry moves fast. Whether it's staying updated with the latest AI tools or mastering a new management methodology, continuous professional development is key. Consider obtaining industry-recognized certifications that align with Sr. Machine Learning Engineer - Finance requirements.
• Networking: Connect with other professionals in similar roles. Join online communities, attend webinars, and engage in meaningful discussions on professional social networks. Often, the best opportunities come through referrals and community engagement.
• Soft Skills Matter: Communication, empathy, and leadership are often the deciding factors between two equally qualified technical candidates. Cultivate these skills as they are universally valued across all industries and seniority levels.

Additionally, research the specific company's culture and values. Tailoring your application to show how you align with their mission can significantly increase your chances of moving forward in the process.

Salary & Compensation

Salary not disclosed; typically competitive for the role.

Work Arrangement

Type: On-Site

Standard business hours at the office.

Comprehensive Application Strategy & Hiring Process

Applying for a new role is a marathon, not a sprint. Follow this strategic approach to maximize your success rate:

1. Initial Research & Tailoring

Don't send the same resume to every employer. Spend at least 30 minutes researching the company. Look for recent news, their product roadmap, and their team structure. Modify your summary and core competencies to reflect the specific keywords found in the job description.

2. The Perfect Cover Letter

If the application allows for a cover letter, use it to tell a story that your resume cannot. Explain why you are passionate about this specific company and how your unique background makes you the perfect fit for the challenges they are currently facing.

3. Navigating the Multi-Stage Interview

Most modern hiring processes involve 3-5 stages. This typically includes a recruiter screen, a technical or skill-based assessment, a peer interview, and a final leadership round. Prepare for each stage differently: focus on enthusiasm and fit for the recruiter, technical depth for the assessment, and strategic vision for the leadership round.

4. Post-Interview Follow-Up

Always send a personalized thank-you note within 24 hours of each interview. Reference a specific topic discussed during the call to demonstrate your active listening and genuine interest in the role.

By following these steps, you demonstrate a high level of professionalism and attention to detail that sets you apart from the average applicant.

Typical Interview Process

1. Resume screening
2. HR call
3. Skill interview
4. Final manager interview
5. Offer

Tip: Research the company's products and culture.

Global Market Intelligence & Relocation Insights

At JobSetuu, we specialize in helping talent navigate the global job market. Here is what you need to know about the current landscape in Global and beyond:

The demand for skilled professionals is increasingly borderless. For roles based in Global, understanding the local cost of living, visa requirements (if applicable), and cultural nuances is vital. If this is a remote role, consider the time zone alignment and the asynchronous communication culture of the hiring organization.

Relocation Support: Many forward-thinking companies offer relocation packages that include moving stipends, temporary housing, and legal assistance with work permits. When evaluating an offer, look beyond the base salary—consider the total compensation package, including equity, bonuses, and healthcare benefits.

Work-Life Balance Trends: Hybrid and remote work have become standard in many regions. Research the local labor laws and common practices regarding work hours and vacation time to ensure the role aligns with your lifestyle goals.

Leveraging JobSetuu's tools can help you compare salaries across different cities and understand the "purchasing power" of your potential offer, ensuring you make an informed decision for your long-term career path.

Skills & Competency Roadmap for Professional Development

To remain competitive in Professional Development, we recommend focusing on the following core competencies over the next 12-18 months:

• Technical Mastery: Deepen your expertise in the core tools and languages relevant to your field. For developers, this might be cloud architecture; for marketers, it might be data-driven attribution modeling.
• AI Augmentation: Learn how to leverage generative AI and automation tools to increase your productivity. Understanding how to integrate these technologies into your workflow is becoming a non-negotiable skill.
• Leadership & Strategy: Even in individual contributor roles, the ability to think strategically and lead projects from inception to completion is highly valued. Focus on stakeholder management and high-level project planning.
• Data Literacy: The ability to interpret data and use it to drive decisions is essential across all business functions. Familiarize yourself with data visualization and basic analytical concepts.

By investing in these areas, you not only prepare yourself for the role you are applying for today but also build a resilient foundation for the opportunities of tomorrow.

Apply via JobSetuu

Discover your next career milestone on JobSetuu. This Sr. Machine Learning Engineer - Finance position is part of our commitment to bringing you the most relevant and high-impact job openings globally. At JobSetuu, we simplify your job search by aggregating premier listings and providing the tools you need to stand out. Don't miss the chance to elevate your professional journey—explore more opportunities and career insights on our platform today.