Senior Machine Learning Engineer, AI Studio

Accountabilities:
The Senior Machine Learning Engineer will lead the development and delivery of production-grade AI solutions, combining advanced engineering practices with responsible AI principles. This role requires ownership across the entire AI lifecycle, including architecture, development, evaluation, deployment, governance, and continuous improvement. Define AI solution objectives by establishing user needs, workflows, decision points, intended use cases, success metrics, acceptance criteria, and measurable outcomes. Evaluate business problems and determine appropriate approaches, including automation, classical machine learning, deep learning, generative AI, retrieval-augmented generation (RAG), AI agents, or alternative solutions. Design and own production architectures across data pipelines, knowledge systems, models, APIs, workflows, user experiences, security frameworks, and human review processes. Develop and maintain production software, machine learning models, NLP solutions, predictive systems, AI workflows, and evaluation pipelines. Build and optimize data-centric AI solutions through feature engineering, experimentation, model validation, and performance improvement. Establish robust evaluation frameworks, including testing methodologies, quality benchmarks, uncertainty analysis, error classification, and release criteria. Implement MLOps and LLMOps capabilities supporting reproducibility, version control, deployment automation, monitoring, governance, and lifecycle management. Partner with security, privacy, legal, quality, and compliance teams to ensure responsible AI implementation and appropriate controls. Create reusable AI capabilities that improve operational efficiency, scalability, and measurable business value. Mentor engineers, promote strong engineering practices, and contribute to continuous improvement across AI development processes. Communicate technical decisions, risks, limitations, and recommendations clearly to technical and non-technical stakeholders. Collaborate with product, engineering, architecture, and business teams to deliver impactful AI-driven solutions. Requirements: The ideal candidate is a senior AI and machine learning professional with experience building production systems and applying advanced technologies to complex business problems. They should combine strong technical expertise with product-oriented thinking and the ability to operate in collaborative, regulated environments. Doctorate degree, or Master’s degree with 2+ years of relevant experience, Bachelor’s degree with 4+ years of relevant experience, Associate’s degree with 8+ years of relevant experience, or equivalent professional experience. Proven experience owning and delivering at least one production machine learning, generative AI, software, data, or automation system with measurable outcomes. Strong hands-on proficiency in Python and SQL, with experience developing production software, services, and evaluation frameworks. Advanced expertise in at least one key area such as applied machine learning, generative AI, RAG systems, AI agents, ML platforms, or MLOps. Experience with advanced machine learning techniques including causal inference, uncertainty modeling, active learning, time-series analysis, survival methods, or drift-aware retraining. Experience with deep learning technologies such as transformers, multimodal systems, neural networks, fine-tuning, model optimization, quantization, or inference acceleration. Knowledge of cloud and AI infrastructure platforms such as AWS, SageMaker, Databricks, Spark, Kubernetes, MLflow, Airflow, Kubeflow, or similar technologies. Experience implementing AI governance, human-in-the-loop workflows, validation processes, and responsible AI practices. Strong understanding of software engineering principles, APIs, data pipelines, and scalable system design. Ability to connect technical decisions with user needs, business value, operational requirements, risks, and costs. Demonstrated technical leadership, mentoring ability, and willingness to remain hands-on. Excellent analytical judgment and communication skills, including the ability to explain complex concepts and trade-offs. Experience collaborating across product, engineering, business, architecture, and compliance teams. Strong ownership mindset with the ability to adapt, solve problems, and continuously improve solutions. Benefits: Competitive annual salary range of $156,190.05 - $211,315.95 USD . Comprehensive employee benefits package including medical, dental, and vision coverage. Retirement and savings plan with company contributions. Life and disability insurance coverage. Flexible spending account options. Annual bonus opportunities based on eligibility. Stock-based long-term incentive opportunities. Generous paid time-off programs. Flexible work models where applicable. Career development opportunities and support for professional growth. Opportunity to work on innovative AI solutions with meaningful real-world impact. Collaborative environment focused on science, technology, and improving patient outcomes.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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