AI/ML Engineer

Company Description

At WorkFox Solutions, we bridge the gap between top talent and forward-thinking companies, helping both grow and thrive. We offer end-to-end recruitment services, executive search, talent acquisition strategies, HR consulting, and personalized career counseling. Our approach combines human intuition with data-driven insights to build trust, transparency, and long-term partnerships. Whether you're an employer searching for the perfect fit or a job seeker looking for your next opportunity, we are here to support your journey.

Role Description

We are seeking a
Senior Consultant – AI & Machine Learning
with
8–10 years of experience
to provide
strategic guidance, technical expertise, and hands-on engineering
for enterprise AI/ML initiatives.

This is
not a pure data science role
— we are looking for an
engineering-focused consultant
who can:

• Partner with data scientists to productionize models.
• Architect and deploy AI/ML solutions using
  modern cloud platforms and MLOps tools.
• Provide
  advisory and technical leadership
  to enterprise stakeholders on generative and agentic AI adoption.
• Drive reliability, automation, and performance across
  mission-critical ML systems
  .
• You'll combine
  deep technical knowledge
  with
  client-facing consulting skills
  , working at the intersection of engineering, strategy, and innovation.

Key Responsibilities

Technical Advisory:
Guide clients on AI/ML strategy, architectures, and tool selection (focus on generative & agentic AI).

Client Engagements:
Support business development by assessing client needs, proposing solutions, and delivering compelling POCs and presentations.

Solution Design & Implementation:
Architect, build, and prototype scalable AI/ML systems using
AWS SageMaker, Azure AI Foundry, Glean, GitHub Copilot, etc.

ML Engineering:

• Design robust
  ML pipelines
  for training, validation, and deployment.
• Transition models from experimentation to production.
• Implement
  high-availability, low-latency model serving
  (REST/gRPC).

MLOps & Automation:

• Automate testing, monitoring, and retraining workflows with
  CI/CD pipelines.
• Implement
  model drift detection, performance monitoring, and governance.

Cloud Expertise:
Deploy and optimize AI/ML workloads on
AWS, Azure (preferred), and optionally GCP
.

Collaboration:
Work with engineering, product, and client teams to align solutions with business value.

Thought Leadership:
Stay ahead of AI/ML trends and contribute to whitepapers, blogs, or client workshops

Must-Have Skills & Experience

Experience:

• 8+ years in AI/ML engineering and consulting.
• Proven record of
  enterprise-grade AI/ML solution delivery.
• Hands-on expertise in
  Agentic AI
  and
  Generative AI platforms.

Technical Skills:

• Strong programming in
  Python
  .
• Proficiency with
  ML frameworks
  (TensorFlow, PyTorch, Scikit-learn, XGBoost).
• Hands-on with
  MLOps tools
  (MLflow, Airflow, TFX, Kubeflow, BentoML).
• Experience with
  containerization
  (Docker, Kubernetes).
• Knowledge of
  cloud services
  :
• AWS (SageMaker, Bedrock, EC2, S3, Lambda).
• Azure (AI Foundry, Cognitive Services, Machine Learning).
• Familiarity with
  data engineering tools
  (Spark, Kafka, SQL/NoSQL).
• Strong grasp of
  CI/CD, Git, Infrastructure-as-Code
  (Terraform, Helm).
• Monitoring & observability (Prometheus, Grafana, ELK).

Certifications:
At least one of:

• AWS Certified Machine Learning – Specialty.
• Microsoft Certified: Azure AI Engineer Associate.

Soft Skills:

• Strong communication & client engagement skills.
• Ability to lead technical discussions with senior stakeholders.
• Critical thinking & problem-solving in ambiguous environments.

Good to Have

• Exposure to
  OpenAI, Anthropic Claude, Hugging Face
  .
• Edge/embedded ML, model quantization, and hardware acceleration.
• Knowledge of
  model governance, compliance, and security
  .
• Domain expertise (finance, healthcare, retail, manufacturing).
• Leadership: mentoring junior engineers, leading cross-functional programs.
• Contributions to open-source AI/ML projects or industry events.

Minimum Qualification

• Bachelor's or Master's degree in
  Computer Science, Engineering, or related field
  .
• 8–10 years of experience in
  ML engineering and AI consulting roles.