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Temporary Neo4J Jobs (NOW HIRING)

Tekwissen

Senior AI/ML Engineer

Frisco, TX · Hybrid

$98K - $134K/yr

Temporary Assignment Work Type: Onsite : Role Overview: * Lead the design and deployment of ... Build customer knowledge graphs (Neo4j/Neptune) modeling users, products, and interactions * Enable ...

Merican

Senior AI/ML Engineer

Atlanta, GA · Hybrid

$100K - $138K/yr

Temporary Assignment Work Type: Onsite Role Overview: * Lead the design and deployment of scalable ... Build customer knowledge graphs (Neo4j/Neptune) modeling users, products, and interactions * Enable ...

Tekwissen

Sr AI Platform Engineer

Bellevue, WA · On-site

$117K - $162K/yr

Temporary Assignment Work Type:Onsite About the role: * You'll join a working squad of senior ... Pinecone, Weaviate, pgvector, Neo4j, or comparable; embeddings and retrieval patterns. * AI ...

Tekwissen

Sr AI Platform Engineer

Atlanta, GA

Temporary Assignment Work Type: Onsite JOB SUMMARY: * You'll join a working squad of senior ... Pinecone, Weaviate, pgvector, Neo4j, or comparable; embeddings and retrieval patterns. * AI ...

Tekwissen

Knowledge Graph Engineer

Frisco, TX · Hybrid

Temporary Assignment Work Type: Hybrid : About the Role: * We are looking for an experienced ... Neo4j migration or comparative architecture experience (trade-offs vs. Neptune at scale). * Python ...

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Senior AI/ML Engineer

Senior AI/ML Engineer

Tekwissen

Frisco, TX • Hybrid

$98K - $134K/yr

Other

Posted 7 days ago

Job description

Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation, information technology and services
Position: Senior AI/ML Engineer
Location: Frisco TX / Atlanta GA
Duration: 6 Months
Job Type: Temporary Assignment
Work Type: Onsite
Job Description :
Role Overview:
  • Lead the design and deployment of scalable AI/ML solutions focused on real-time personalization, recommendation systems, and customer knowledge graphs, driving measurable improvements in engagement and conversion.
Key Responsibilities:
  • Design and build collaborative, content-based, and hybrid recommendation systems
  • Develop real-time personalization pipelines and ranking models
  • Architect end-to-end ML systems (batch + streaming) with low-latency inference
  • Build customer knowledge graphs (Neo4j/Neptune) modeling users, products, and interactions
  • Enable Customer 360 insights and context-aware recommendations
  • Develop scalable pipelines using Python, Spark, Kafka
  • Implement feature engineering, model training, and deployment workflows
  • Drive experimentation (A/B testing) and optimize for CTR, engagement, and conversion
  • Ensure data quality, model performance, and system reliability
  • Apply MLOps practices (CI/CD, monitoring, model lifecycle management)
  • Mentor team members and collaborate with product/business stakeholders
Required Skills:
  • Strong Python and experience with Pandas, PySpark
  • Expertise in recommender systems (matrix factorization, deep learning, ranking models)
  • Experience in entity resolution / record linkage
  • Hands-on with graph modeling & graph databases (Neo4j, RDF, graph embeddings)
  • Strong understanding of ML lifecycle, experimentation, and evaluation metrics (NDCG, MAP, Precision/Recall)
Nice to Have:
  • Experience with real-time ML systems and large-scale data (TB/PB)

TekWissen® Group is an equal opportunity employer supporting workforce diversity.
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About TekWissen

Sourced by ZipRecruiter

TekWissen is an emerging global human capital, recruitment and IT services organization. Operating since 2009, we draw upon more than a decade of staffing experience to deliver critical talent acquisition solutions and IT engagements for our clients. We’re founded on a culture that is passionate about delivering tailored solutions, that create lasting partnerships.

Industry

Recruiting and staffing services

Company size

501 - 1,000 Employees

Headquarters location

Ann Arbor, MI, US

Year founded

2009

Social media

Twitter

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