Design and deploy deep learning systems for search ranking, personalized recommendations, geospatial search, and pickup-point selection. Translate business goals into ML objectives, lead offline and online evaluation, conduct A/B tests, and partner with engineering on production model serving and latency optimization. Own the production ML lifecycle, including monitoring, drift detection, retraining pipelines, and quality management across international markets.
Geo Search runs the search that tens of millions of customers use to say where they are going, across many countries where the commercial maps everyone else leans on are often wrong, incomplete, or simply missing. We are building our own search and recommendation stack, which means we own the data, the ranking, and the measurement. The team is cross-functional, spanning backend, machine learning, mobile, and QA, and works with a product manager focused on relevance and with geo analysts. It owns place search and autocomplete, geocoding, ranking and personalization, location detection and pickup selection, and its own search screens on Android and iOS. It is measured on order conversion, search conversion, and mean reciprocal rank
We are looking for a Senior Data Scientist to own ranking, relevance and recommendation for geo search: the models that decide which places a customer sees, in what order, and how that changes with context.
We are looking for a Senior Data Scientist to own ranking, relevance and recommendation for geo search: the models that decide which places a customer sees, in what order, and how that changes with context.
This is a modeling role with production responsibility, and it is close to a founding one. You will define how relevance is measured here, build the training data from scratch, and own the models that follow. The interesting constraint is that suggestions must return within tens of milliseconds of each keystroke, in cities where map data is thin and people type in mixed scripts, so model choice is an evidence-based trade-off you will own rather than a preference: gradient-boosted ranking on behavioral data today, transformers and large language models where they earn their place in query understanding and cross-script matching, and neural reranking if the failure analysis justifies it. Ground truth comes from what drivers, couriers and customers actually do, and from completed rides, so a large part of the craft is turning messy behavioral logs into labels you can trust. You will measure your impact through offline evaluation and online A/B tests, and changes reach millions of customers in weeks.
Key Responsibilities
- Own ranking, relevance and recommendation for geo search end to end, from training data through to models serving in production
- Build the label pipeline that turns search sessions and completed rides into trustworthy training data, including correction for position bias and other presentation effects
- Train and own the models that order results, and the confidence model that decides per query whether we serve our own answer or fall back to an external provider
- Build query understanding for our markets, including cross-script matching, using large language models to label offline and distilling into models fast enough for the keystroke path
- Own evaluation end to end: the offline replay harness that scores recorded sessions against real rides, the error analysis that turns failures into work for the right team, and the online experiments that prove impact
- Keep models healthy after launch as data and cities shift
Skills, Knowledge and Expertise
Minimum qualifications
- 5 or more years building models that shipped and improved a production metric
- Direct experience with ranking, search relevance, or recommendation systems, including how they are evaluated
- Expert Python and SQL, fluency with gradient boosting, and working knowledge of transformers
- Experience taking a model to production and owning it afterwards
- The ability to work across teams, since search quality work generates data and engineering tasks that others own
Preferred qualifications - Depth in geocoding, autocomplete, or place search
- Learning to rank in practice: pairwise and listwise objectives, MRR, NDCG, Hit@k, and their failure modes
- Relevance tuning on OpenSearch or Elasticsearch, including analyzers
- Multilingual or cross-script search, for example Arabic and Arabizi or Urdu and Roman Urdu
- Distilling language models under a latency budget, and experience in mapping or geospatial products in developing markets
Why join us
- Help us challenge injustice by creating fair choices for millions of people across 47 countries.
- Develop your professional skills with access to mentoring, career consulting, and learning programs.
- Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program.
- Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects.
- Work alongside people who take initiative, speak openly, and challenge themselves to grow.
- Improve your language skills through co-financed courses and internal speaking clubs.
Final benefits may vary depending on the location.
About
inDrive is a global tech company on a mission to challenge injustice through fair choices. We started in 2012 in the coldest city on Earth, when a group of friends created a way for people to agree on fair ride prices. That idea grew into one of the world’s top ride-hailing apps, now with 400M installs across 47 countries.Today, we offer more than rides: from freight and delivery to intercity travel and financial services, all designed to put people first. We are committed to having a positive impact on people’s lives both through our core business, which supports local communities via a fair pricing model; and through the work of our impact programs. Ready to ignite your inner drive?
Similar Jobs
Artificial Intelligence • Big Data • Cloud • Information Technology • Software • Cybersecurity • Data Privacy
Leads Enterprise Security services, setting and enforcing security standards across identity, endpoints, business applications, cloud infrastructure, networking, IoT, and automation. Partners with IT, SOC, vulnerability management, governance, and threat operations teams to secure applications, monitor environments, manage EDR policies, remediate vulnerabilities, assess risks, and maintain compliance. Also drives AI security initiatives and uses AI tools to improve enterprise security capabilities and team efficiency.
Top Skills:
AWSAzureCircleCIEdrFedrampGCPGithub ActionsGleanGoHashicorp VaultIso 27001JAMFJavaLastpassLinuxmacOSMicrosoft IntuneOktaPowershellPythonSalesforceSoc 2TinesWindowsZapier
Artificial Intelligence • Cloud • Information Technology • Energy • Infrastructure as a Service (IaaS)
Owns the operating model connecting data center asset activity in Nuvolo with fixed asset records in NetSuite. Designs processes, data standards, workflows, integrations, controls, reconciliations, reporting, and exception management. Partners with asset management, accounting, IT, and system owners to ensure asset additions, replacements, transfers, retirements, disposals, and maintenance events are properly documented and routed for accounting review.
Top Skills:
CmmsErpMaximoNetSuiteNuvoloServicenow EamSoxTririga
Software • Defense
Lead international partnership execution across defense and operational markets. Activate commercial, technical, and delivery partner capabilities within customer opportunities, build repeatable partnership frameworks, and align with Growth, Sales, Product, Technical, and Finance teams. Analyze partner performance and market constraints, develop scaling business cases, and represent Onebrief with senior military, government, enterprise, and coalition stakeholders. The role requires extensive domestic and international travel and potential security clearance eligibility.
Top Skills:
ConfluenceHubspotJIRANotionOnebrief PlatformPartner Relationship Management (Prm) PlatformsSalesforceSlack
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
