Product Engineering Manager - Commercial Pharma US Targeting, Recommendation, Optimization and Measurement
Genentech · South San Francisco, CA
- Level
- Manager
- Team
- Manufacturing
- Base pay
- $150k–$278k
- Degree
- Preferred
- Experience asked
- 5+ years
- Industry
- Pharma & life sciences
- Posted
- 30+ days ago
The role in 30 seconds
A management manufacturing role at Genentech (pharma & life sciences) in South San Francisco, CA. Define the architectural roadmap and select digital technologies for enterprise-level customer engagement.
- They ask for
- 5+ years · degree preferred
- Tools it names
- Lean
- Base pay
- $150k–$278k
Read from the posting. The full description is below.
From the plant jobs report · week of November 2, 2026
Manufacturing Engineer roles in California: typical posted base $111k–$173k. This one lists $150k–$278k.
Median of the low and high ends of 165 live postings that list pay, out of 436 manufacturing engineer openings in California, read from manufacturers' own careers sites.
California plant jobs report →Pay by team and state →What moves pay →
How this role compares
Against 435 other live manufacturing postings in California.
- Base pay
- About 59% above similar roles
- Experience asked
- Typical (5+ years)
Typical $109k–$159k, from 143 postings that list pay.
Similar roles usually ask 5+ years.
Skills these teams ask for most
- Tooling 50%
- New product launch 44%
- Root cause 37%
- Automation 35%
- Machining 27%
- CATIA / NX 26%
✓ = this posting asks for it too. % = share of similar postings that mention it.
At a glance
Pulled from the posting text. If it's not listed here, the posting didn't say.
How to get in at this plant
Five moves over a week or two. The first one takes ten minutes.
- 1
Pick 2–3 people on the Manufacturing team at Genentech
Engineers who joined in the last year or two reply the most. Use the team search on this page to find them.
- 2
Send a short, curious note
One real question about their work. No favors yet. Each person gets a different note, written for this role.
- 3
Turn a reply into a short call
Questions worth asking about this team:
- What does a normal week look like on your team?
- Is the work mostly new product launches or sustaining existing lines?
- How much time do you spend on the floor versus at a desk?
- How did you land the job? What stood out in your interviews?
- 4
Apply with someone vouching for you
If the call went well, ask whether they’d pass your résumé to the hiring manager. Send your résumé link, apply that day, and let them know.
- 5
Bring proof to the interview
One page of before-and-after numbers from projects you led: scrap, OEE, cycle time, cost. Plant managers hire on results.
This plant: Genentech in South San Francisco
3 other open roles at this site.
- Lead Automation Engineer, Autonomous Lab Science & Technology · Controls · Manager
- QMS Process Engineer · Process
- Senior Director, Business Operations & Portfolio Controls · Controls · Director+
Full description from GenentechAs posted on their careers site.ShowHide
Key Responsibilities
- ◆Define the architectural roadmap and select digital technologies for enterprise-level customer engagement. Ensure engineering output meets ROI and adoption targets.
- ◆Partner with Business Product Owners to translate roadmaps into high-fidelity technical plans for segmenting, "what-if" simulations, and attribution modeling.
- ◆Mentor team members on long-term career paths. Build a future-focused talent portfolio by balancing technical skills with healthy team dynamics.
- ◆Oversee end-to-end delivery performance across the product group. Resolve systemic, cross-functional roadblocks and drive process re-engineering to boost efficiency.
- ◆Manage the team budget (headcount, vendors, operations) and strategically allocate resources across the portfolio to maximize impact.
Who You Are
- ✓Bachelor’s degree in Engineering, Science, or Business (Master’s preferred).
- ✓5+ years in people leadership or program management; 2+ years in Pharma/Biotech or regulated healthcare.
- ✓Proven track record in deploying BI solutions (predictive/prescriptive), modern visualization tools, and ML/AI toolsets.
- ✓A servant leader (VACC) with an enterprise mindset, capable of navigating ambiguity and breaking down organizational silos.
- ✓Strong business acumen, lean/agile mindset, and the ability to empower autonomous teams while maintaining accountability.
Benefits
Relocation benefits are not available for this job posting.
#RDT2026
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The Position
Product Engineering Manager - Commercial Pharma US Targeting, Recommendation, Optimization and Measurement
Roche Digital Technology (RDT) is where innovation meets purpose. As a global team at the heart of Roche, we are a community of business-minded technologists committed to help shape tomorrow’s digital future of healthcare. Our mission is to power Roche through cutting-edge digital technologies, harnessing the potential of artificial intelligence, data, and scalable tech innovations. Driven by purpose and passion, we’re building a future where digital is a core strength across all of Roche, enabling smarter ways of working, unlocking human potential, and driving breakthroughs that truly matter for millions of patients around the world.
The Opportunity
As a Product Engineering Manager of Commercial Pharma US Targeting, Recommendation, Optimization and Measurement, you will sit at the intersection of cutting-edge technology and life-changing medicine.
You will lead a team responsible for architecting scalable digital solutions that transform commercial intent into business impact while fostering a high-performing, sustainable engineering culture. This role partners closely with the Genentech business product owners that support key business commercial functions of measurement (e.g., segmenting HCPs, dynamic lists, geospatial analysis etc.), recommendation (e.g., Next Best Action), optimization (e.g., measurable ROI, “what-if” simulations etc.) and Measurement (e.g., Attribution modeling, operational health etc.).
Actual title will be Team Lead Engineering Commercial Pharma US Targeting, Recommendation, Optimization and Measurement.