AI Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Engineer on a 4+ month remote contract, offering expertise in Python, SQL, and cloud platforms (AWS, Azure). Requires 3-6 years of experience in AI, data engineering, and analytics, with preferred certifications in machine learning.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
August 27, 2025
πŸ•’ - Project duration
More than 6 months
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🏝️ - Location type
Remote
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
United States
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🧠 - Skills detailed
#Databases #Big Data #Storytelling #Cloud #Spark (Apache Spark) #Hadoop #Tableau #Visualization #Pandas #Data Storytelling #NLP (Natural Language Processing) #ML (Machine Learning) #Data Architecture #PyTorch #Agile #SageMaker #AI (Artificial Intelligence) #Deep Learning #AWS (Amazon Web Services) #Aurora RDS #Computer Science #Microsoft Power BI #SQL (Structured Query Language) #Statistics #RDS (Amazon Relational Database Service) #Data Engineering #Synapse #BI (Business Intelligence) #NumPy #Data Modeling #Data Exploration #Oracle #PySpark #Athena #Azure #Data Science #Python #Aurora #"ETL (Extract #Transform #Load)" #Scala #TensorFlow #Data Pipeline #Redshift
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Turing IT Labs, is seeking the following. Apply via Dice today! HI, Job Title: AI Engineer Location: Remote Duration: 4+ Months Contract Job Description: About The Role We are seeking a highly motivated AI Engineer to join as a Practice Hire, where the candidate will contribute across multiple client engagements, internal initiatives, and practice development activities. This role is designed for professionals with strong expertise in data engineering, analytics, machine learning, and Generative AI who can thrive in fast-paced, cross-functional environments. The ideal candidate has proven experience in building scalable data pipelines, deploying predictive and generative AI models, and delivering business insights through data storytelling and visualization. This role provides opportunities to work with modern cloud platforms (AWS, Azure) and advanced ML/AI technologies, including LLMs and generative AI solutions. Job Responsibilities β€’ Design, develop, and optimize data pipelines (ETL/ELT) to support scalable data architectures. β€’ Build, train, and deploy machine learning and generative AI models for diverse business use cases. β€’ Conduct statistical analysis, data exploration, and feature engineering to improve model performance. β€’ Develop interactive dashboards and reports using tools such as Power BI and Tableau. β€’ Collaborate with business stakeholders to translate complex data findings into actionable insights. β€’ Automate workflows to reduce manual effort and improve efficiency across projects. β€’ Contribute to practice-level knowledge sharing, frameworks, and accelerators. β€’ Stay current with advancements in cloud-based data solutions, ML/AI, and generative AI practices. Mandatory Skills β€’ Strong experience in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow) and SQL (Redshift, Aurora, RDS, Oracle). β€’ Proven knowledge of cloud ecosystems (AWS, Azure) including services like SageMaker, Glue, Athena, Synapse Analytics, and Data Factory. β€’ Expertise in data modeling, statistical analysis, applied machine learning, and generative AI. β€’ Experience with BI tools (Power BI, Tableau) for KPI reporting and visualization. β€’ Strong understanding of ETL/ELT workflows and data warehousing concepts. β€’ Ability to work in Agile environments and collaborate effectively with cross-functional teams. Preferred Skills β€’ Deep expertise in Generative AI (LLMs, Transformer models, Prompt Engineering, Fine-tuning). β€’ Experience in Natural Language Processing (NLP) and advanced deep learning methods. β€’ Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG). β€’ Experience in CI/CD pipelines and MLOps practices. β€’ Knowledge of big data tools (PySpark, Hadoop, EMR). β€’ Strong business acumen and ability to connect data insights to organizational goals. Education β€’ Master s degree in Data Science, AI, Computer Science, Statistics, or related field preferred. β€’ Bachelor s degree in Engineering, Computer Science, Data Science, or related field required. Certifications β€’ AWS Certified Machine Learning / Data Engineer / AI Practitioner or equivalent preferred. β€’ Certifications in Generative AI or LLM-related platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI) are a plus. Required Experience β€’ 3 6 years of hands-on experience in AI, data science, data engineering, and analytics. β€’ Proven track record in deploying ML and generative AI models and building end-to-end AI solutions. β€’ Strong communication skills with the ability to present complex technical concepts to non-technical audiences.