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Entry Level Ran Optimization Engineer Jobs in Austin, TX

... ensure optimal performance and cost metrics across the platform. Responsibilities : • Run ... what you ran. Qualifications : Required : • 8+ years of professional software engineering ...

This entry-level role assists in the design, development, and implementation of renewable energy ... Support solar PV and renewable project layouts, site optimization, and entitlement processes ...

Renewable Project Engineer

Austin, TX · On-site

$80K - $105K/yr

This entry-level role assists in the design, development, and implementation of renewable energy ... layouts, site optimization, and entitlement processes. • Assist with engineering reports ...

This position serves as an entry level role within the company, offering potential for development ... optimal performance. * Perform any other duties as assigned, contributing to the success of various ...

... optimization, and stabilization of complex manufacturing processes across all phases of product ... This role evolves from entry-level learning and support to senior technical leadership and ...

... and optimizing RAG pipelines - Leading technical discovery in fast-paced environments ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Role: Adobe AEM with Java programming Location: Austin, TX onsite AEM Engineer with Java ...       - Query optimization       - Debugging level       ...

Role: Adobe AEM with Java programming Location: Austin, TX onsite AEM Engineer with Java ... Dispatcher caching - Query optimization - Debugging level Infrastructure - Cronjob setup ...

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Entry Level Ran Optimization Engineer information

See Austin, TX salary details

$29.7K

$68.8K

$117K

How much do entry level ran optimization engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for entry level ran optimization engineer in Austin, TX is $68,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,000.00 and $77,800.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Ran Optimization Engineer vs Network Optimization Technician?

AspectEntry Level Ran Optimization EngineerNetwork Optimization Technician
CredentialsBachelor's in Telecommunications, Electrical Engineering, or related fieldAssociate's or Bachelor's in Networking, Telecommunications, or related field
Work EnvironmentTelecom companies, network providers, field and office settingsTelecom companies, network service providers, field and lab environments
Industry UsageCommonly used in mobile network planning and optimizationUsed in maintaining and troubleshooting network performance

Entry Level Ran Optimization Engineers focus on optimizing radio access network parameters to improve coverage and capacity, often working with LTE/5G networks. Network Optimization Technicians handle network performance issues, troubleshooting, and maintenance. While both roles require telecommunications knowledge, the Engineer role emphasizes planning and optimization, whereas Technicians focus on operational support and problem resolution.

What are the most commonly searched types of Ran Optimization Engineer jobs in Austin, TX? The most popular types of Ran Optimization Engineer jobs in Austin, TX are:
What are popular job titles related to Entry Level Ran Optimization Engineer jobs in Austin, TX? For Entry Level Ran Optimization Engineer jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Entry Level Ran Optimization Engineer jobs in Austin, TX look for? The top searched job categories for Entry Level Ran Optimization Engineer jobs in Austin, TX are:
What cities near Austin, TX are hiring for Entry Level Ran Optimization Engineer jobs? Cities near Austin, TX with the most Entry Level Ran Optimization Engineer job openings:
Infographic showing various Entry Level Ran Optimization Engineer job openings in Austin, TX as of May 2026, with employment types broken down into 4% Full Time, and 96% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $68,752 per year, or $33.1 per hour.
Lakehouse Performance Engineer

Lakehouse Performance Engineer

IBM

Austin, TX • On-site

Full-time

Posted 3 days ago


IBM rating

7.9

Company rating: 7.9 out of 10

Based on 72 frontline employees who took The Breakroom Quiz

95th of 184 rated software companies


Job description

Job Summary:
IBM is a leader in AI-powered, cloud-native products, and they are looking for a Lakehouse Performance Engineer to enhance the performance of their watsonx.data platform. The role involves benchmarking, workload engineering, and performance observability to ensure optimal performance and cost metrics across the platform.
Responsibilities:
• Run, maintain, and continuously improve reproducible benchmarks across watsonx.data configurations and against competitive offerings.
• Build and curate workload suites that reflect real customer query mixes, data volumes, concurrency profiles, and freshness requirements: not just synthetic benchmarks.
• Ensure every published result is reproducible end-to-end: controlled environments, pinned versions, locked datasets, documented methodology, variance analysis, and statistically defensible reporting.
• Operationalize the canonical price‑performance KPIs ($/query, $/TB scanned, $/training‑token, queries/sec/$, TCO at workload mix); instrument workloads, collect data, and produce repeatable scorecards.
• Build and maintain the metrics, traces, profiles, GPU/CPU utilization, query plan, and IO telemetry that flow from benchmark runs into the performance data store.
• Develop dashboards that surface trends, regressions, and competitive position to engineering, leadership, and external audiences.
• Operate performance regression gates in CI/CD; triage failures, file and drive issues with engine, storage, and GPU teams, and verify fixes.
• Drill into slow queries and GPU/CPU bottlenecks using profilers (Nsight, perf, async-profiler, pprof, flamegraphs) and query plan inspection to pinpoint regressions and improvement opportunities.
• Own the lifecycle of the dedicated performance environment(s) supporting watsonx.data: GPU and CPU clusters, networking, storage, and the orchestration that schedules workloads onto them.
• Build and maintain infrastructure-as-code (Terraform/Ansible/Helm) for provisioning, configuring, and resetting test environments deterministically across on-prem hardware and cloud (IBM Cloud and partner clouds).
• Develop and operate the benchmark harness itself: job scheduler, run orchestration, dataset provisioning, result capture, artifact storage, and the API/CLI other teams use to launch runs.
• Own the curated datasets used for benchmarking and the warehouse of historical results that powers trend analysis, regression detection, and competitive comparisons.
• Manage capacity and utilization of the performance lab so concurrent campaigns from different teams (query engine, storage, GPU acceleration, AI) run cleanly and without interference.
• Provide engineers across watsonx.data with self-service paths to run standardized perf experiments against well-known baselines, lowering the cost of evidence-based engineering decisions.
• Pair with engineers on the query engine, storage, GPU acceleration, catalog, and AI/RAG paths to land performance improvements and verify their impact.
• Produce data, charts, and write-ups that feed internal quarterly scorecards and external performance whitepapers, blog posts, and analyst briefings.
• Participate in design reviews and code reviews where performance is at stake; flag risks early and propose measurable acceptance criteria.
• Document workloads, harnesses, lab usage, and results so the next engineer internal or external: can reproduce what you ran.
Qualifications:
Required:
• 8+ years of professional software engineering experience with at least 2 years focused on performance engineering, benchmarking, or SRE for a data platform, database, distributed system.
• Strong programming skills in at least one of Python, Go, Java, plus comfort with shell scripting and modern automation tooling.
• Working knowledge of at least one modern analytics engine (Presto/Trino, Spark, DuckDB, ClickHouse, or comparable) and at least one open table format (Iceberg, Delta, or Hudi).
• Hands-on experience with at least some of: Linux performance tooling (perf, ftrace, eBPF), profilers (Nsight, async-profiler, pprof), and query plan analysis.
• Infrastructure-as-code fluency in at least one of Terraform, Ansible, Pulumi, or Helm; comfort writing and maintaining the automation, not just consuming it.
Preferred:
• Hands-on experience with GPU-accelerated data processing (RAPIDS/cuDF, Velox/Theseus‑class engines, CUDA) and the GPU memory hierarchy (HBM, NVLink, PCIe trade‑offs).
• Experience publishing or co-authoring peer-reviewed or industry-recognized performance results (TPC, MLPerf, ClickBench, LST‑Bench, or similar).
• Experience operating a multi-tenant performance lab or shared test fleet where multiple teams ran experiments concurrently.
• Experience building bespoke benchmark harnesses or workload generators, including dataset generation at TB+ scale.
• Familiarity with vector search, retrieval-augmented generation (RAG), and AI inference/training performance characterization.
• Familiarity with FinOps and cloud unit economics—translating raw performance numbers into $/performance and TCO conclusions.
• Contributions to relevant open-source projects (Iceberg, Trino, Spark, Arrow, Velox, RAPIDS, OpenTelemetry, perf-tooling, etc.).
• Hands-on experience designing and running performance experiments: controlling for variance, isolating variables, and producing clear, defensible results.
• Experience operating real infrastructure: Linux servers, Kubernetes, container runtimes, networking basics, and object storage.
• Comfort with observability tooling: metrics (Prometheus), tracing/telemetry (OpenTelemetry), and dashboards (Grafana or equivalent).
Company:
IBM provides technology and consulting, including software, infrastructure systems, and cloud-based solutions. Founded in 1911, the company is headquartered in Armonk, USA, with a team of 10001+ employees. The company is currently Late Stage.

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About IBM

Sourced by ZipRecruiter

At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Armonk, NY, US

Year founded

1911

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