Why Join careeraxis?
At careeraxis, we are redefining the future of health‑focused retail and digital pharmacy services. With a legacy that dates back over a century, we have grown from a single storefront into a nationwide network of thousands of locations and millions of daily customers. Our mission is simple yet powerful: to improve lives through better health. By leveraging cutting‑edge technology—especially in artificial intelligence, natural language processing (NLP), and cloud‑based solutions—we deliver seamless, omnichannel experiences that connect people with the care they need, wherever they are.
Our virtual workforce is a cornerstone of this transformation. As a remote‑first organization, we empower talent from every corner of the country to collaborate, innovate, and make a tangible impact on the health of our communities. If you are passionate about AI, love solving complex data challenges, and thrive in a flexible, high‑performance environment, careeraxis is the place where your expertise will shape the next generation of health‑tech solutions.
Position Overview
We are seeking an experienced AI/ML Operations Engineer to lead the design, deployment, and continuous improvement of our conversational AI and data‑entry pipelines. This role sits at the intersection of data science, software engineering, and product delivery, ensuring that our voice‑ and text‑based NLP models operate reliably at scale across cloud and edge environments. You will partner with data scientists, product managers, and engineering teams to translate cutting‑edge research into production‑ready services that power real‑time decision‑making for our customers.
Key Responsibilities
- End‑to‑End Model Lifecycle Management: Own the full MLOps workflow—from data ingestion, model training, and validation to CI/CD deployment, monitoring, and automated rollback.
- Cloud Architecture & Deployment: Design and implement scalable, secure cloud infrastructure (Azure, AWS, or Google Cloud) for hosting NLP models, ensuring high availability and low latency for voice and text interactions.
- Model Optimization: Continuously improve model performance, throughput, and cost‑efficiency through quantization, pruning, and hardware‑specific tuning.
- Data Pipeline Engineering: Build robust data pipelines that handle multimodal inputs (audio, text, metadata), perform feature extraction, and feed clean, labeled data into training loops.
- Quality Assurance & Testing: Develop automated testing frameworks, conduct A/B experiments, and validate model outputs against business KPIs such as accuracy, sentiment detection, and user satisfaction.
- Collaboration & Knowledge Sharing: Work closely with data scientists, NLP researchers, and front‑end engineers to integrate models into product features, and mentor junior team members on best practices in MLOps.
- Monitoring & Incident Response: Implement real‑time monitoring dashboards, set up alerts for drift or degradation, and lead rapid incident response to maintain service reliability.
- Research & Innovation: Stay current with the latest advancements in AI, NLP, speech‑to‑text, and voice biometrics, and evaluate emerging technologies for potential adoption.
- Compliance & Security: Ensure all AI solutions comply with HIPAA, GDPR, and other relevant regulations, incorporating data encryption, access controls, and audit trails.
- Travel (Optional): Up to 10% travel for occasional on‑site collaboration, industry conferences, or client workshops.
Essential Qualifications
- Education: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience).
- Experience: Minimum 2 years of professional experience in AI/ML, specifically with NLP, speech processing, or conversational AI.
- Programming Proficiency: Expert‑level skills in Python, SQL, and at least one deep‑learning framework (TensorFlow, PyTorch, or similar).
- Cloud & MLOps Expertise: Hands‑on experience deploying models on cloud platforms (Azure, AWS, GCP) and using CI/CD tools such as GitHub Actions, Jenkins, or Azure DevOps.
- Data Engineering: Proven ability to design and maintain data pipelines using tools like Apache Airflow, Kafka, or Spark.
- Domain Knowledge: Familiarity with healthcare data standards, medical terminology, or prior experience in the health‑care or retail pharmacy sector is highly desirable.
- Communication: Strong written and verbal communication skills; ability to translate technical concepts for non‑technical stakeholders.
- Flexibility: Willingness to work remotely with a self‑directed, results‑oriented mindset.
Preferred Qualifications & Skills
- Master’s or Ph.D. in Computer Science, Computational Linguistics, Electrical Engineering, or a related discipline.
- Experience with speech‑to‑text, speaker identification, sentiment analysis, or voice biometrics.
- Knowledge of model interpretability techniques (SHAP, LIME) and bias mitigation strategies.
- Familiarity with containerization (Docker, Kubernetes) and serverless architectures.
- Exposure to multilingual NLP, especially Spanish language models.
- Background in retail or health‑care operations, understanding of pharmacy workflows and patient engagement.
- Leadership experience managing cross‑functional projects or small technical teams.
Core Competencies for Success
- Analytical Thinking: Ability to dissect complex problems, identify root causes, and devise data‑driven solutions.
- Innovation Mindset: Proactive in exploring new algorithms, tools, and processes that can give careeraxis a competitive edge.
- Collaboration: Comfortable working in a distributed team, building strong relationships across product, design, and business units.
- Quality Focus: Commitment to rigorous testing, documentation, and continuous improvement.
- Adaptability: Thrive in a fast‑changing environment where priorities shift based on emerging business needs.
Career Growth & Learning Opportunities
At careeraxis, your career trajectory is shaped by your ambition and the impact you create. As an AI/ML Operations Engineer, you will have access to:
- Mentorship from senior AI researchers and industry veterans.
- Sponsored certifications (e.g., Azure AI Engineer Associate, Google Professional Machine Learning Engineer).
- Opportunities to lead high‑visibility projects that directly affect millions of customers.
- Cross‑functional rotations into product management, data science, or architecture roles.
- Participation in internal hackathons, research symposiums, and external conferences.
Work Environment & Culture at careeraxis
We believe that great work stems from a supportive, inclusive, and empowering culture. Our remote‑first policy is backed by:
- Flexible Hours: Choose a schedule that aligns with your peak productivity while meeting core collaboration windows.
- Collaborative Tools: State‑of‑the‑art communication platforms, virtual whiteboards, and shared code repositories to keep teams connected.
- Diversity & Inclusion: A commitment to building a workforce that reflects the communities we serve, with employee resource groups and inclusive hiring practices.
- Well‑Being Programs: Access to mental‑health resources, virtual fitness classes, and wellness stipends.
- Recognition & Rewards: Regular acknowledgment of achievements through spot awards, performance bonuses, and career‑milestone celebrations.
Compensation, Perks & Benefits
While exact figures vary based on experience and location, successful candidates can expect a competitive salary range of $35,000–$40,000 per year, complemented by a comprehensive benefits package that includes:
- Health, dental, and vision insurance with low employee contributions.
- Retirement savings plan with company match.
- Paid time off, holidays, and flexible sick leave.
- Professional development budget for courses, certifications, and conferences.
- Technology stipend for home‑office setup (ergonomic chair, monitor, high‑speed internet).
- Employee assistance program and confidential counseling services.
- Volunteer time off to support community health initiatives.
Application Process
Ready to bring your AI expertise to a purpose‑driven organization? Follow these steps to apply:
- Prepare your updated resume, highlighting relevant AI/ML projects, cloud deployments, and any healthcare‑related experience.
- Gather supporting documents: degree certificates, transcripts, and a recent passport‑size photo.
- Complete the online application form (link provided below) and attach all required files.
- Submit your application and await a confirmation email from the careeraxis recruiting team.
Our hiring team reviews applications on a rolling basis, so early submission is encouraged.
Interview Preparation Tips
We value authenticity and curiosity. To help you succeed, consider preparing answers for the following common interview topics:
- Describe a challenging AI model you built, the obstacles you faced, and how you overcame them.
- Explain your approach to monitoring model drift in a production environment.
- Share an example of a time you collaborated with a cross‑functional team to deliver a product feature.
- Discuss how you stay current with emerging AI research and translate it into practical solutions.
- Reflect on your strengths, areas for growth, and how they align with the mission of careeraxis.
Join the careeraxis Family
At careeraxis, every line of code you write, every model you deploy, and every insight you generate contributes to healthier lives across the nation. If you are driven by purpose, eager to work with cutting‑edge technology, and thrive in a remote, collaborative setting, we want to hear from you.
Apply today and become a catalyst for change in the health‑tech landscape.
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