Job#: 3026858
Job Description:
12+ Month Contract
Remote
$70-93/HR
Position Description:
Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions — including Generative AI and Large Language Model (LLM) systems — in areas such as computer vision, perception, localization, natural language processing, and conversational AI. They automate and optimize the end-to-end ML and Gen AI model lifecycle using expertise in experimental methodologies, statistics, prompt engineering, and coding for tool building and analysis. Design and develop innovative ML models, Gen AI systems, and software algorithms — including LLM-based architectures (, transformer models, RAG pipelines, fine-tuned foundation models) — to solve complex business problems in both structured and unstructured environments
Skills Required:
GCP, Big Data, Artificial Intelligence & Expert Systems, API 1. GCP – Experience deploying and managing services on Google Cloud Platform, including Compute Engine, Cloud Storage, IAM, and Cloud Functions. For example, designing and implementing a cloud-native application architecture using GKE (Google Kubernetes Engine) with Cloud SQL and Pub/Sub. 2. Big Data – Experience working with large-scale data processing frameworks such as Apache Spark, Dataflow, or BigQuery. For example, building ETL pipelines that process terabytes of daily event data and transform it for downstream analytics. 3. Data Warehousing – Experience designing and maintaining data warehouse solutions (, BigQuery, Snowflake, Redshift). For example, modeling a star schema for a retail analytics platform that supports reporting on sales, inventory, and customer behavior. 4. Artificial Intelligence & Expert Systems – Experience developing or integrating AI/ML models and rule-based expert systems. For example, building a classification model using Vertex AI to predict customer churn, or implementing a rule engine that automates underwriting decisions. 5. API – Experience designing, building, and consuming RESTful or gRPC APIs. For example, developing a versioned REST API with OAuth authentication that serves as the integration layer between a mobile application and backend microservices.
Skills Preferred:
Google Cloud Platform 1. Google Cloud Platform – Familiarity with advanced GCP services beyond core compute and storage, such as Vertex AI, Dataflow, Cloud Composer (Airflow), and BigQuery ML. For example, using Cloud Composer to orchestrate scheduled data pipelines that feed into a BigQuery data warehouse.
Experience Required:
Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides. 10+ years in IT; 8+ years in development
Experience Preferred:
* Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. * Proven experience in building and deploying RAG systems, including the use of **Vector Databases**. * Proficiency in Python programming. * Solid experience with SQL for data manipulation and querying. * Hands-on experience with Google Cloud Platform (GCP) services relevant to AI/ML. * Basic understanding and practical experience with Machine Learning model fine-tuning. * Familiarity with data engineering concepts and practices. * Expertise in prompt engineering techniques for interacting with LLMs. * Experience with the OpenAI SDK. * Experience developing robust APIs, preferably with **FastAPI**. * Proficiency with **version control systems (, Git)**. * Experience with **containerization technologies (, Docker)**.
Education Required:
Bachelor's Degree
Education Preferred:
Certification Program
Additional Safety Training/Licensing/Personal Protection Requirements:
Additional Information :
1. Design, build, maintain, and optimize scalable ML and Gen AI pipelines, architecture, and infrastructure, including vector databases, embedding stores, and LLM serving layers 2. Use machine learning and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis, and deep learning methods, alongside prompt engineering, retrieval-augmented generation (RAG), and parameter-efficient fine-tuning (PEFT/LoRA) to develop and evaluate algorithms that improve product/system performance, quality, data management, and accuracy 3. Adapt machine learning and Gen AI capabilities to domains such as virtual reality, augmented reality, object detection, tracking, classification, terrain mapping, intelligent document processing, and AI-powered agent workflows 4. Train, fine-tune, and re-train ML models and LLMs as required, including supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning 5. Deploy ML models, LLMs, and AI agents into production; run simulations and evaluations (including LLM evals and red-teaming) for algorithm development and test various scenarios 6. Automate model deployment, training, re-training, and Gen AI pipeline orchestration, leveraging principles of agile methodology, CI/CD/CT, MLOps, and LLMOps — including guardrail integration, prompt versioning, and observability tooling 7. Enable model management for model versioning, traceability, and governance — including responsible AI practices, bias evaluation, hallucination mitigation, and content safety controls — to ensure modularity and consistency across environments for both ML and Gen AI systems
Compensation & Benefits
The anticipated pay range for this position is $ to $ Access to health, dental, and vision benefits, along with a 401(k) plan, is available.
This employer is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
Apex uses a virtual recruiter as part of the application process. Click here for more details.
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Apex Systems is a world-class IT services company that serves thousands of clients across the globe. When you join Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRated's Best of Staffing® in Talent Satisfaction in the United States and Great Place to Work® in the United Kingdom and Mexico. Apex uses a virtual recruiter as part of the application process. Click here for more details.
Apex Benefits Overview: Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our ‘Welcome Packet’ as well, which an Apex team member can provide.