Title: Senior AI/ML Engineer
Company Name: Spectrum IT Solutions Ltd.
Vacancy: 1
Age: 26 to 38 years
Location: Dhaka (Banglamotor)
Salary: Negotiable
Experience:
∎ At least 4 years
∎ The applicants should have experience in the following business area(s):Software Company, IT Enabled Service
Published: 28 Jun 2025
Education:
∎ Bachelor of Science (BSc) in Computer Science & Engineering
Requirements:
Additional Requirements:
∎ Age 26 to 38 years
∎ 4+ years in AI/ML engineering with demonstrable leadership of production deployments.
∎ Expert in Python and core ML libraries (PyTorch, TensorFlow, Hugging Face Transformers).
∎ Proven experience in architecting and monitoring multi‑agent AI systems and orchestrated workflows.
∎ Deep expertise in tokenization, embeddings, sequence modelling, ASR, and TTS integration.
∎ Strong background in designing scalable ETL/ELT pipelines; proficient with SQL, NoSQL, and big‑data tools (Spark, Kafka).
∎ Hands‑on with containerization (Docker), orchestration (Kubernetes), and serverless platforms (AWS Lambda, Azure Functions, GCP Cloud Run).
∎ Skilled in CI/CD for ML, model registry/versioning (MLflow, DVC), observability (Prometheus, Grafana), and automated retraining.
∎ Strong problem‑solving and architectural design skills.
∎ Excellent communication and stakeholder management—able to distill complex technical topics for diverse audiences.
∎ Familiarity with reinforcement learning (e.g., RLHF) or sequential decision‑making frameworks is desirable.
∎ Experience with conversational AI platforms (LangChain, Rasa, Dialogflow) or telephony integrations (Twilio, SIP) is a plus.
∎ Must‑Have Skills & Experience:
∎ 4+ years in AI/ML engineering with demonstrable leadership of production deployments.
∎ Expert in Python and core ML libraries (PyTorch, TensorFlow, Hugging Face Transformers).
∎ Proven experience in architecting and monitoring multi‑agent AI systems and orchestrated workflows.
∎ Deep expertise in tokenization, embeddings, sequence modelling, ASR, and TTS integration.
∎ Strong background in designing scalable ETL/ELT pipelines; proficient with SQL, NoSQL, and big‑data tools (Spark, Kafka).
∎ Hands‑on with containerization (Docker), orchestration (Kubernetes), and serverless platforms (AWS Lambda, Azure Functions, GCP Cloud Run).
∎ Skilled in CI/CD for ML, model registry/versioning (MLflow, DVC), observability (Prometheus, Grafana), and automated retraining.
∎
∎ Additional requirements:
∎ Strong problem‑solving and architectural design skills.
∎ Excellent communication and stakeholder management—able to distill complex technical topics for diverse audiences.
∎ Familiarity with reinforcement learning (e.g., RLHF) or sequential decision‑making frameworks is desirable.
∎ Experience with conversational AI platforms (LangChain, Rasa, Dialogflow) or telephony integrations (Twilio, SIP) is a plus.
Responsibilities & Context:
∎ Define and articulate the technical roadmap for AI/ML products, aligning with business goals.
∎ Evaluate emerging AI technologies and frameworks; recommend adoption strategies and proof‑of‑concepts.
∎ Architect highly scalable, fault‑tolerant agentic AI workflows and microservice ecosystems.
∎ Establish best practices for model versioning, deployment patterns (blue/green, canary), and rollback strategies.
∎ Lead advanced NLP/LLM fine‑tuning, Retrieval‑Augmented Generation (RAG) systems, and multi‑agent orchestration.
∎ Drive performance tuning of ASR/TTS pipelines (e.g., Whisper, Kaldi, Tacotron) for real‑time, low‑latency voice interactions.
∎ Oversee design of robust data ingestion, feature engineering, and labeling frameworks at scale.
∎ Implement end‑to‑end CI/CD and CI/CT workflows for ML assets using tools like Jenkins, GitHub Actions, and MLflow.
∎ Define SLAs/SLIs for AI services; integrate monitoring (Prometheus, Grafana) and automated drift detection.
∎ Lead incident response, root‑cause analysis, and post‑mortems for AI system failures.
∎ Mentor and coach mid/junior‑level engineers; lead code reviews and design discussions.
∎ Partner with DevOps, product managers, and stakeholders to translate requirements into deliverables.
∎ Technical Leadership & Strategy:
∎ Define and articulate the technical roadmap for AI/ML products, aligning with business goals.
∎ Evaluate emerging AI technologies and frameworks; recommend adoption strategies and proof‑of‑concepts.
∎
∎ Architecture & System Design:
∎ Architect highly scalable, fault‑tolerant agentic AI workflows and microservice ecosystems.
∎ Establish best practices for model versioning, deployment patterns (blue/green, canary), and rollback strategies.
∎
∎ Model Development & Optimization:
∎ Lead advanced NLP/LLM fine‑tuning, Retrieval‑Augmented Generation (RAG) systems, and multi‑agent orchestration.
∎ Drive performance tuning of ASR/TTS pipelines (e.g., Whisper, Kaldi, Tacotron) for real‑time, low‑latency voice interactions.
∎
∎ Data & MLOps Pipeline Ownership:
∎ Oversee design of robust data ingestion, feature engineering, and labeling frameworks at scale.
∎ Implement end‑to‑end CI/CD and CI/CT workflows for ML assets using tools like Jenkins, GitHub Actions, and MLflow.
∎
∎ Production Monitoring & Reliability:
∎ Define SLAs/SLIs for AI services; integrate monitoring (Prometheus, Grafana) and automated drift detection.
∎ Lead incident response, root‑cause analysis, and post‑mortems for AI system failures.
∎
∎ Team Mentorship & Collaboration:
∎ Mentor and coach mid/junior‑level engineers; lead code reviews and design discussions.
∎ Partner with DevOps, product managers, and stakeholders to translate requirements into deliverables.
Skills & Expertise:
Compensation & Other Benefits:
∎ Tour allowance
∎ Salary Review: Yearly
∎ Lunch Facilities: Full Subsidize
∎ Festival Bonus: 2
∎ Lead transformative AI initiatives with significant autonomy and ownership.
∎ Collaborative, growth‑driven culture emphasizing continuous learning and innovation.
∎ Lead transformative AI initiatives with significant autonomy and ownership.
∎ Collaborative, growth‑driven culture emphasizing continuous learning and innovation.
Workplace:
∎ Work at office
Employment Status: Full Time
Job Location: Dhaka (Banglamotor)
Job Highlights:
∎ We're seeking an energetic, target-driven Senior AI/ML Engineer with at least 4 years of experience in leading production deployments.
∎ Apply now or send your CV to [email protected] with the subject: "Senior AI/ML Engineer Application".
Read Before Apply:
Spectrum IT Solutions Ltd. delivers cutting‑edge software and AI solutions across industries. We empower teams to push technological boundaries, building high‑impact products that solve real‑world challenges.
Learn more at https://spectrum.com.bd.
Apply now or send your CV to [email protected] with the subject line "Senior AI/ML Engineer Application".
| University | Percentage (%) |
|---|---|
| East West University | 7.38% |
| BRAC University | 7.38% |
| 5.74% | |
| Daffodil International University (DIU) | 4.10% |
| North South University | 4.10% |
| American International University Bangladesh (AIUB) | 4.10% |
| Begum Rokeya University, Rangpur | 3.28% |
| Jahangirnagar University | 3.28% |
| Islamic University, Bangladesh | 2.46% |
| University of Dhaka | 1.64% |
| Age Range | Percentage (%) |
|---|---|
| 20-30 | 70.49% |
| 31-35 | 18.85% |
| 36-40 | 3.28% |
| 40+ | 2.46% |
| Salary Range | Percentage (%) |
|---|---|
| 0-20K | 3.28% |
| 20K-30K | 13.93% |
| 30K-40K | 12.30% |
| 40K-50K | 19.67% |
| 50K+ | 50.82% |
| Experience Range | Percentage (%) |
|---|---|
| 0 years (Freshers) | 39.34% |
| 0.1 - 1 years | 10.66% |
| 1.1 - 3 years | 16.39% |
| 3.1 - 5 years | 18.03% |
| 5+ years | 15.57% |