Today’s List at a Glance
A hand-picked list of top-tier roles for ambitious professionals. Here’s the breakdown:
- 💰 Salary Range: $64K – $318K
- 🏢 Top Companies Hiring: Apple, Genentech, Lumen
- 📍 Geographic Spread: 1 remote position, with on-site roles in hubs like Cupertino, CA and Madrid, IA.
- 🪜 Seniority Level: Focus on senior and leadership roles (Tech Lead, Solution Architect, Senior Responsible AI) with one internship entry-path.
Featured Responsible AI & Governance Roles
Data Scientist in Responsible AI at Genentech
📍 Location: Madrid, IA
💰 Salary: $90K – $130K
Why it’s a great opportunity: Direct Responsible AI role at a major biotech company focused on ethical AI implementation and governance — ideal for professionals wanting to shape ethics practices in life sciences.
Solution Architect – AI Governance & Ethics at Genentech
📍 Location: Madrid, IA
💰 Salary: $100K – $130K
Why it’s a great opportunity: Hands-on architect role centering on building platforms and processes for ethical AI deployment — perfect for senior practitioners who want to operationalize governance at scale.
Intern – TITLE – AI Governance at Lumen
📍 Location: US-Anywhere (Remote)
💰 Salary: $64K – $95K
Why it’s a great opportunity: Remote AI Governance internship offering practical exposure to fairness, compliance, and governance workflows — an excellent entry point for aspiring ethics officers.
AIML – Tech Lead ML Engineer, Responsible AI at Apple
📍 Location: Cupertino, CA
💰 Salary: $181K – $318K
Why it’s a great opportunity: Senior leadership role combining ML engineering and safety/ethics responsibility at a top-tier technology company — high impact and high visibility.
Is your resume ready to beat the bots? Before you apply, run it through our free ATS Resume Scanner to see your compatibility score!
Strategic Playbook for Landing These Roles
Profile of an Ideal Candidate
- Core Responsibility: Design, implement, and govern production AI systems to ensure they are safe, fair, auditable, and compliant with internal and external policies.
- Essential Experience: A strong background in applied machine learning or data science combined with hands-on experience in AI governance, fairness/bias mitigation, or MLOps; senior roles expect leadership of cross-functional programs and platform work.
- Key Competencies: Beyond technical prowess, these roles demand exceptional communication, stakeholder management, and the ability to translate ethical frameworks into engineering requirements and measurable controls.
The Resume Blueprint: Keywords & Metrics
Keywords to Target:
AI Governance
Fairness & Bias Mitigation
Model Risk Assessment
MLOps / Productionization
Metrics that Matter:
✅ Reduced model bias by 20–40% through targeted fairness interventions and metric-driven retraining, measured across protected cohorts.
✅ Deployed governance controls across 10+ models, implementing automated checks and lineage tracking that lowered policy incidents by X% (insert your figure).
✅ Improved model reliability by 30% with monitoring and alerting (latency, drift, data-quality), shortening incident-to-resolution time.
Nailing the Narrative: Your Interview Strategy
Be prepared to answer tough, strategic questions. Here are some specific examples:
“Walk me through a time you discovered bias in a production model. What diagnostics did you run, what interventions did you choose, and how did you validate the fix?”
“Describe how you’d design an AI governance program for a business unit that currently has no model controls. What are the first three measurable steps you’d take?”
“Give an example of a technical trade-off you made between model performance and fairness or safety. How did you decide and present that trade-off to stakeholders?”
