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It Search Jobs (NOW HIRING)

6AM City, LLC

WI · On-site

$85 - $110/hr

Sales tax (accruals, remittance, exemptions) preferred Thomas Edwards Group is an Executive Search Firm specializing in the direct hire and interim placement of Accounting, Finance, HR and IT ...

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IT Search

supervisor

Yonkers, NY · On-site

Manufacturing Supervisor with CC Setup/ Programming exp Open$$'s Benefits: annual and quarterly bonus program, 401k, health, dental, vision, tuition reimbursement, vacation/sick paid time off Onsite ...

Thomas Edwards Group

Bookkeeper

Arlington, TX · On-site

$30 - $40/hr

Familiarity with Paychex payroll system Company Description Thomas Edwards Group is an Executive Search Firm specializing in the direct hire and interim placement of Accounting, Finance, HR and IT ...

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$32.5K

$75.5K

$110.5K

How much do it search jobs pay per year?

As of Aug 21, 2026, the average yearly pay for it search in the United States is $75,500.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,500.00 and $91,500.00 per year, depending on experience, location, and employer.

What is an IT search specialist?

An IT Search specialist is a professional who focuses on finding and recruiting qualified candidates for information technology positions within organizations. They often work for recruitment agencies or in-house HR departments and use various tools and networks to locate, screen, and recommend IT talent. Their role involves understanding technical job requirements, sourcing candidates through online platforms, and managing the hiring process from initial contact to final placement. IT Search specialists play a key role in helping companies fill critical tech roles efficiently and effectively.

What are the key skills and qualifications needed to thrive as an IT search specialist?

To thrive as an IT Search Specialist, you need strong knowledge of IT roles and technologies, recruitment processes, and sourcing strategies, usually supported by experience in technical recruiting or HR. Familiarity with applicant tracking systems (ATS), Boolean search techniques, and professional networking platforms like LinkedIn is essential. Excellent communication, relationship-building, and critical thinking skills help you connect with candidates and hiring managers effectively. These competencies ensure you can identify and attract top IT talent, matching organizational needs with the right expertise.

What are some common challenges faced by professionals in IT search and how can they be addressed?

Professionals in IT search often face challenges such as rapidly changing job requirements, high competition for top tech talent, and the need to quickly adapt to new technologies. To overcome these, it's important to stay updated on industry trends, build strong relationships with both clients and candidates, and leverage advanced sourcing tools and platforms. Regular training, networking, and collaborating closely with hiring managers can also enhance effectiveness and help meet the evolving demands of the role.
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What states have the most It Search jobs?

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What job categories do people searching It Search jobs look for?

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It Search jobs near you
Infographic showing various It Search job openings in the United States as of August 2026, with employment types broken down into 75% Full Time, 20% Part Time, and 5% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $75,500 per year, or $36.3 per hour.

Machine Learning/ Search Engineer - Services Special Projects

Socket.dev

Cupertino, CA • On-site

$180 - $240/hr

Other

Posted 16 days ago

Job description

DESCRIPTION

Our team is building a massive, real-time search experience from the ground up — one that will reach users at Apple scale. It's search at the intersection of Generative AI and Information Retrieval, and it's a rare opportunity to shape a product that millions will rely on. We are seeking a highly experienced and innovative Search Systems Engineer to help design, develop, and optimize large-scale search systems.

MINIMUM QUALIFICATIONS
  • Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or a related field 10+ years of experience in Machine Learning, Data Science, or Software Engineering roles with a significant focus on search infrastructure and information retrieval. Hands on experience building and deploying large-scale search systems in production. Deep understanding of information retrieval, query understanding, query augmentation and multi-stage ranking algorithms Strong foundation in deep learning architectures for search and retrieval (e.g., transformers, cross encoder models, graph neural networks, learned sparse representations). Experience with to multi-objective optimization in search systems (e.g., relevance, diversity, freshness, fairness). Experience with real-time systems, user feedback loops, and model retraining pipelines. Strong proficiency in Go, Java, C++ and Python Proven experience with ML frameworks including PyTorch, XGBoost. Familiarity with cloud environments (including AWS) and containerization (Docker, Kubernetes) Extensive experience working with data processing pipelines including Spark, Flink Hands-on experience with vector search including FAISS Familiarity with streaming platforms including Apache Kafka Experience with search infrastructure including OpenSearch, and/or Elasticsearch Hands-on experience deploying, serving, and optimizing LLMs, Embeddings and ML models directly in the production query/request path Past successful deployments with tuning of models (including quantization) for performance and quality optimization Excellent communication skills and a collaborative mindset
PREFERRED QUALIFICATIONS
  • Master's Degree; PhD Preferred Published work or patents in the domain of search systems, information retrieval, or related ML fields. Experience with graph databases such as TigerGraph Experience with data and model versioning tools and practices (e.g., DVC, MLflow, Weights & Biases) Deep Experience with KV Stores including SSTables and Cassandra Experience with tuning KV-cache and batching for low-latency, high-throughput real-time inference. Deep production level experience with inference runtimes/compilers (ONNX Runtime, TensorRT/TensorRT-LLM), and serving frameworks (vLLM, SGLang or Triton, TorchServe ) .
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