Senior Machine Learning Engineer / GraphDB / Contract-to-Hire

Job Description

Our client?is a technology-driven company specializing in innovative solutions that empower organizations to harness the power of data and machine learning. With expertise in advanced analytics, cloud computing, and cutting-edge technologies like graph data science, they develop scalable, intelligent systems to solve complex business challenges. Dedicated to delivering value through innovation, the company serves a diverse range of industries, including healthcare, finance, and government sectors.

They are currently seeking a highly skilled and experienced Senior Machine Learning Engineer with a strong background in graph data science and machine learning as a service (MLaaS) to join their team. In this role, you will leverage your expertise to design, develop, and deploy advanced machine learning solutions that utilize graph-based techniques and cloud-based MLaaS platforms. Collaborating with multidisciplinary teams, you will solve complex challenges, enhance data-driven decision-making, and contribute to high-impact projects in a fast-paced, collaborative environment.

This is a fully remote, contract-to-hire position that requires US Citizenship. Public Trust clearance will be required/sponsored, with potential need for higher clearances down the road.?

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Key Responsibilities
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• Design and implement scalable machine learning models with a focus on graph data science, leveraging graph-based algorithms and tools to solve business-critical problems.
• Utilize graph databases (e.g., Neo4j, TigerGraph) to model, query, and analyze complex relationships within data.
• Develop, optimize, and maintain end-to-end machine learning pipelines, incorporating MLaaS solutions from cloud providers (AWS SageMaker, Google Vertex AI, Azure ML, etc.).
• Collaborate with data scientists to preprocess and analyze graph-structured data, extracting meaningful insights and relationships.
• Deploy machine learning models in production environments and ensure their scalability, performance, and reliability.
• Mentor junior engineers and provide technical leadership in graph data science, MLaaS, and machine learning best practices.
• Stay current with advancements in machine learning, graph data science, and related technologies to recommend and implement innovative solutions.
• Partner with software engineers to integrate machine learning and graph data science solutions into existing applications and workflows.
• Identify and address technical risks and challenges while adhering to project deadlines and objectives.

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Required Skills/Qualifications
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• Bachelor's or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field (Ph.D. preferred).
• US Citizenship. Current Public Trust clearance preferred, but not required.?
• 6+ years of professional experience in machine learning, data science, or related roles.
• Proficiency in Python, R, or similar programming languages, with expertise in machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Extensive experience with graph data science techniques and tools (e.g., Graph Neural Networks, PageRank, community detection) and graph databases (e.g., Neo4j, TigerGraph).
• Knowledge of cloud-based MLaaS platforms, including deployment, monitoring, and optimization of machine learning models using AWS SageMaker, Google Vertex AI, or Azure ML.
• Strong understanding of statistical modeling, data mining, and deep learning techniques.
• Hands-on experience with big data tools and frameworks such as Spark, Hadoop, or similar.
• Proficiency in containerization tools (Docker) and orchestration platforms (Kubernetes) for deploying ML solutions.
• Previous experience working with graph data in domains such as fraud detection, social network analysis, or drug discovery is highly desirable.

? The Offer
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• Competitive salary and equity offering.
• Comprehensive health, dental, and vision insurance.
• 401(k) with company match.
• Flexible hybrid work environment.
• Opportunities for professional development and career growth.
• *Applicants must be currently authorized to work in the US on a full-time basis now and in the future.**

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